Publications

[Google Scholar profile]

The papers which are not available here due to copyright limitations can be obtained by sending email to jussi _dot_ tohka _at_ uef _dot_ fi

If the paper is published in open-access, just click the name of the journal/conference to get the paper.  Most of them are.  I also include links to preprints if such has been posted to biorxiv, arxiv, or alike. The content of the preprints most often matches exactly or almost exactly the published article.   

Scientific monographs:

J. Tohka. Deformable Surface Models in Medical Image Analysis: Automatic surface extraction using deformable meshes. VDM Verlag Dr. Muller, Saarbrucken, Germany, 2009, 200 pages. [Amazon.com][Amazon.co.uk]

J. Tohka. Global optimization-based deformable meshes for surface extraction from medical images, PhD dissertation, Tampere University of Technology, Finland, 2003 (Publications of Tampere University of Technology 432). [Abstract] , [ps], [pdf]

Submitted preprints (these manuscripts have not yet appeared in journals/conferences):

1. J. Tohka , F.E. Pollick, J. Pajula, J.-P. Kauppi. Comparing fMRI inter-subject correlations between groups. [BioRxiv 370023]

2. Bryan A. Strange, Linda Zhang, Alba Sierra-Marcos, Eva Alfayate, Jussi Tohka, Miguel Medina. Predicting the future development of mild cognitive impairment in the cognitively healthy elderly. [BioRxiv 2020.07.30.227496]

3. Morteza Ghahremani, Mohammad Khateri, Alejandra Sierra, Jussi Tohka. Adversarial Distortion Learning for Medical Image Denoising. arXiv:2204.14100

4. Vandad Imani, Carlos Sevilla-Salcedo, Elaheh Moradi, Vittorio Fortino, Jussi Tohka. Multi-Objective Genetic Algorithm for Multi-View Feature Selection. arXiv:2305.18352 

Refereed articles in international journals: 

1. Elaheh Moradi, Mithilesh Prakash, Anette Hall, Alina Solomon, Bryan Strange, Jussi Tohka. Machine learning prediction of future amyloid beta positivity in amyloid-negative individuals. Alzheimer's Research and Therapy, 16, 46, 2024 [BioRxiv 10.1101/2023.07.17.547202] 

2. Mohammad Khateri, , Morteza Ghahremani, , Alejandra Sierra, and Jussi Tohka . No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy. IEEE Transactions on Computational Imaging, 2024, in press [Arxiv]

3. Nurmirinta, T.A.T., Turunen, M.J., Korhonen, R.K., Tohka, J., Liukkonen M.K, Mononen, M.E. Two-Stage Classification of Future Knee Osteoarthritis Severity After 8 Years Using MRI: Data from the Osteoarthritis Initiative. Ann Biomed Eng (2024) 

4. Mara Quach,  Idrish Ali,  Sandy R. Shultz,  Pablo M. Casillas-Espinosa,  Matthew R. Hudson,  Nigel C. Jones,  Juliana C. Silva,  Glenn R. Yamakawa,  Emma L. Braine,  Riikka Immonen,  Richard J. Staba,  Jussi Tohka,  Neil G. Harris,  Olli Gröhn,  Terence J. O'Brien,  David K. Wright. ComBating inter-site differences in field strength: harmonizing preclinical traumatic brain injury MRI data. NMR in Biomedicine. 2024;e5142. doi:10.1002/nbm.5142  

5. Juan Miguel Valverde, Artem Shatillo, Jussi Tohka. Sauron U-Net: Simple automated redundancy elimination in medical image segmentation via filter pruning. Neurocomputing 594,127817,2024. 

6.  John D. Lewis, Vandad Imani, Jussi Tohka. Intelligence and cortical morphometry: caveats in brain-behavior associations. Brain Structure and Function 229, pages 1417 - 1432, 2024. 

7. Ricardo Coronado-Leija, Ali Abdollahzadeh, Hong-Hsi Lee, Santiago Coelho, Benjamin Ades-Aron, Ying Liao, Raimo A Salo, Jussi Tohka, Alejandra Sierra, Dmitry S Novikov, Els Fieremans. Volume electron microscopy in injured rat brain validates white matter microstructure metrics from diffusion MRI. Imaging Neuroscience, 2: 1 - 20, 2024. 

8. Carlos Platero, Jussi Tohka and Bryan Strange. Estimating Dementia Onset: AT(N) Profiles and Predictive Modeling in Mild Cognitive Impairment Patients, Current Alzheimer Research 20:11: 778 - 790, 2023. 

9. Marta Garo-Pascual, Christian Gaser, Linda Zhang, Jussi Tohka, Miguel Medina, Bryan A Strange. Brain structure and phenotypic profile of superagers compared with age-matched older adults: a longitudinal analysis from the Vallecas Project. The Lancet Healthy Longevity, 4(8)e374-e385, 2023. 

10. Sweta Bhagavatula, Ryan Cabeen, Neil G Harris, Olli Gröhn, David K Wright, Rachael Garner, Alexis Bennett, Celina Alba, Aubrey Martinez, Xavier Ekolle Ndode-Ekane, Pedro Andrade, Tomi Paananen, Robert Ciszek, Riikka Immonen, Eppu Manninen, Noora Puhakka, Jussi Tohka, Mette Heiskanen, Idrish Ali, Sandy R Shultz, Pablo M Casillas-Espinosa, Glenn R Yamakawa, Nigel C Jones, Matthew R Hudson, Juliana C Silva, Emma L Braine, Rhys D Brady, Cesar E Santana-Gomez, Gregory D Smith, Richard Staba, Terence J O'Brien, Asla Pitkänen, Dominique Duncan. Image data harmonization tools for the analysis of post-traumatic epilepsy development in preclinical multisite MRI studies. Epilepsy Research 195: 107201, 2023.

11. Juan Miguel Valverde, Jussi Tohka. Region-wise Loss for Biomedical Image Segmentation. Pattern Recognition 136, 109208, 2023. [arXiv:2108.01941] [Software]

12. M-K Koskinen, MA Laine, A Abdollahzadeh, A Gigliotta, G Mazzini, SH Journée, V Alenius, K Trontti, J Tohka, P Hyytiä, A Sierra, I Hovatta. Node of Ranvier remodeling in chronic psychosocial stress and anxiety. Neuropsychopharmacol. (2023). [bioRxiv 2022.04.05.487090 ]

13. M. Beter, A. Abdollahzadeh, H. H. Pulkkinen, H. Huang, F. Orsenigo, P. U. Magnusson, S. Ylä-Herttuala, J. Tohka & J. P. Laakkonen. SproutAngio: an open-source bioimage informatics tool for quantitative analysis of sprouting angiogenesis and lumen space. Sci Rep 13, 7279 (2023). [Software zenodo]  [Software GitHub]

14. Isabel San Martín Molina, Michela Fratini, Gaetano Campi, Manfred Burghammer, Tilman A. Grünewald, Raimo A. Salo, Omar Narvaez, Manisha Aggarwal, Jussi Tohka, and Alejandra Sierra. A Multiscale Tissue Assessment in a Rat Model of Mild Traumatic Brain Injury. Journal of Neuropathology and Experimental Neurology, 82(1): 71 - 83, 2023. 

15. Juan Miguel Valverde, Artem Shatillo, Riccardo de Feo, Jussi Tohka. Automatic Cerebral Hemisphere Segmentation in Rat MRI with Ischemic Lesions via Attention-based Convolutional Neural Networks. Neuroinformatics, 21(1): 57 - 70, 2023. (open access) [ arXiv:2108.01941] [Software] [Trained models] 

16. Riccardo De Feo, Elina Hämäläinen, Eppu Manninen, Riikka Immonen, Juan Miguel Valverde, Xavier Ekolle Ndode-Ekane, Olli Gröhn, Asla Pitkänen*, Jussi Tohka*.Convolutional Neural Networks Enable Robust Automatic Segmentation of the Rat Hippocampus in MRI After Traumatic Brain Injury . Front. Neurol. 13:820267, 2022. *joint senior authors (open-access) [Software] [bioRxiv 2021.08.03.454863]

17. Eppu Manninen, Karthik Chary, Riccardo De Feo, Elina Hämäläinen, Pedro Andrade, Tomi Paananen, Alejandra Sierra, Jussi Tohka, Olli Gröhn, Asla Pitkänen. Acute Hippocampal Damage as a Prognostic Biomarker for Cognitive Decline but not for Epileptogenesis after Experimental TBI, Biomedicines, 10, 2721, 2022.  

18. Mohammad Khateri, Marco Reisert, Alejandra Sierra, Jussi Tohka, Valerij G. Kiselev. What Does FEXI Measure? NMR in Biomedicine 35(12):e4804, 2022 [arXiv 2202.00496]  [Selected as cover image]

19. I. San Martin Molina, R.A. Salo, O. Gröhn,  J. Tohka,and A. Sierra. Histopathological modeling of status epilepticus-induced brain damage based on in vivo diffusion tensor imaging in rats,  Front Neurosci 2022 Jul 29;16:944432. doi: 10.3389/fnins.2022.944432. eCollection 2022.

20. Carlo Sevilla Salcedo, Vandad Imani, Pablo Olmos, Vanessa Gomez Verdejo, Jussi Tohka. Multi-task longitudinal forecasting with missing values on Alzheimer's Disease, Computer Methods and Programs in Biomedicine 226: 107056, 2022 [arxiv 2201.05040]

21. Budhachandra Khundrakpam, Linda Booij, Seun Jeon, Jussi Tohka, Alan C. Evans. Individualized prediction of future cognition using baseline developmental changes in cortical anatomy. NeuroImage Reports 2(4): 10012, 2022  [bioRxiv 2021.07.05.451172]. 

22. Nikita Mikhailov, Kseniia Koroleva, Ali Abdollahzadeh, Raisa Giniatullina, Oleg Gafurov, Tarja Malm, Alejandra Sierra, Jussi Tohka, Francesco Noe, Rashid Giniatullin. The role of the meningeal lymphatic system in local inflammation and trigeminal nociception implicated in migraine pain. Scientific Reports, 12, 8804, 2022 [bioRxiv 2020.04.25.060939]

23. Riccardo De Feo, Eppu Manninen, Karthik Chary, Elina Hämäläinen, Riikka Immonen, Pedro Andrade, Xavier Ekolle Ndode-Ekane, Olli Gröhn, Asla Pitkänen*, Jussi Tohka*. Hippocampal position and orientation as prognostic biomarkers for posttraumatic epileptogenesis: An experimental study in a rat lateral fluid percussion model. Epilepsia 63(7): 1849 - 1861, 2022;. *joint senior authors (open-access)

24. A. Behanova, A. Abdollahzadeh, I. Belevich, E. Jokitalo, A. Sierra*, J. Tohka*. gACSON software for automated segmentation and morphology analyses of myelinated axons in 3D electron microscopy. Computer Methods and Programs in Biomedicine, 106802, 2022.  *joint senior authors (open access) [arXiv] [Software] [Data] [Special issue website]

25. R. Ciszek, E. Manninen, O. Gröhn, J. Tohka, A. Pitkänen. Machine-Learning Approach to Discover Novel Biomarkers of Posttraumatic Epilepsy. Jasper's Basic Mechanisms of the Epilepsies, 5th edition (accepted), 2022.

26. A. Abdollahzadeh, I. Belevich, E. Jokitalo, A. Sierra*, J. Tohka*. DeepACSON automated White Matter Segmentation in 3D electron microscopy. Communications Biology 4(1): 1 - 14 , 2021.  *joint senior authors  (open access) [bioRxiv 828541] [Software] [Data] 

27. R.V. Marinescu, ..., J. Tohka, R. Ciszek, ..., D. C. Alexander.  The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up,  Machine Learning for Biomedical Imaging, December 2021 issue, arXiv: 2002.03419.

28. Marja Koskuvi, Šárka Lehtonen, Kalevi Trontti, Meike Keuters, Ying Chieh Wu, Hennariikka Koivisto, Anastasia Ludwig, Lidiia Plotnikova, Pekka L. J. Virtanen, Noora Räsänen, Satu Kaipainen, Ida Hyötyläinen, Hiramani Dhungana, Raisa Giniatullina, Ilkka Ojansuu, Olli Vaurio, Tyrone D. Cannon, Jouko Lönnqvist, Sebastian Therman, Jaana Suvisaari, Jaakko Kaprio, Markku Lähteenvuo, Jussi Tohka, Rashid Giniatullin, Claudio Rivera, Iiris Hovatta, Heikki Tanila, Jari Tiihonen, Jari Koistinaho.Contribution of astrocytes to familial risk and clinical manifestation of schizophrenia.  Glia 70(4):650 - 660, 2022. (open access) [BioRxiv 2020.10.23.350413]

29. Juan Miguel Valverde, Vandad Imani, Ali Abdollahzadeh, Riccardo De Feo, Mithilesh Prakash, Robert Ciszek, Jussi Tohka. Transfer Learning in Magnetic Resonance Brain Imaging: a Systematic Review, Journal of Imaging 7(4):66, 2021 (open access) [arXiv preprint arXiv:2102.01530]

30. E. Manninen K. Chary, N. Lapinlampi, P. Andrade de Abreu, T. Paananen A. Sierra, J. Tohka, O. Gröhn and A. Pitkänen. Acute Thalamic Damage as a Prognostic Biomarker for Post-Traumatic Epileptogenesis. Epilepsia, 62(8):1852 – 1864, 2021.

31. Karthik Chary, Omar Narvaez, Raimo A. Salo, Isabel San Martín Molina, Jussi Tohka, Manisha Aggarwal, Olli Grohn, Alejandra Sierra. Microstructural tissue changes in a rat model of mild traumatic brain injury. Frontiers in Neuroscience Nov 26;15:746214, 2021. (open access) 

32. V. Imani, M. Prakash, M. Zare, J. Tohka. Comparison of single and multitask learning for predicting cognitive decline based on MRI data. IEEE Access 9: 154275 - 154291, 2021. (open access) 

33. M. Timmins, I.C. van der Schaaf, E. Bennink, Y. M. Ruigrok, X. An, M. Baumgartner, P. Bourdon, R.De Feo, T. Di Noto, F. Dubost, A. Fava-Sanches, X. Feng, C. Giroud, Inteneural Group, M. Hu, P.F. Jaeger, J.Kaiponen, M. Klimont, Y. Li, H. Li, Y. Lin, T. Loehr, J. Ma, K.H. Maier-Hein, G. Marie, B. Menze, J. Richiardi,S. Rjiba, D. Shah, S. Shit, J. Tohka, T. Urruty, U. Walinska, X. Yang, Y. Yang, Y. Yin, B. K. Velthuis, H.J. Kuijf.Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: TheADAM challenge.NeuroImage, Volume 238,118216, 2021. (open access)

34. J. Tohka and M. van Gils. Evaluation of machine learning algorithms for Health and Wellness applications: a tutorial. Computers in Biology and Medicine, 132: 104324, 2021. (open access) [arXiv:2008.13690]

35. A. Abdollahzadeh, A. Sierra, J. Tohka. Cylindrical Shape Decomposition Algorithm for 3D Segmentation of tubular objects. IEEE Access 9:23979 -23995, 2021 (open access)  arXiv:1911.00571  

36. Riccardo De Feo, Artem Shatillo, Alejandra Sierra, Juan Miguel Valverde, Olli Gröhn, Federico Giove, Jussi Tohka. Automated skull-stripping and segmentation with Multi-Task U-Net in large mouse brain MRI databases. NeuroImage 229, 117734 (open access) [BioRxiv 2020.02.25.964015] [Software] [Tutorial] 

37. Aija Kotila, Jussi Tohka, Jukka-Pekka Kauppi, Ilaria Gabbatore, Leena Mäkinen, Tuula Hurtig, Hanna Ebeling, Vesa Korhonen, Vesa Kiviniemi, Soile Loukusa. Neural-level associations of non-verbal pragmatic comprehension in young Finnish autistic adults. International Journal of Circumpolar Health, 2021 (in press)

38. Paolo Miocchi,  Alejandra Sierra; Laura Maugeri,  Eleonora Stefanutti; Ali Abdollahzadeh; Fabio Mangini; Marta Moraschi; Inna Bukreeva; Lorenzo Massimi; Francesco Brun; Jussi Tohka; Olli Gröhn; Alberto Mittone; Alberto Bravin; Charles Nicaise, Federico Giove; Alessia Cedola, and Michela Fratini. Steerable3D: an ImageJ plugin for neurovascular enhancement in 3-D segmentation.  Physica Medica 81: 197 - 209, 2021.

39. A. Yakubova,  Y. Davidyuk,  J. Tohka, O. Khayrutdinova, I. Kudryavtsev, D. Nurkhametova, A. Kamshilin, R. Giniatullin and A. Rizvanov  Searching for Predictors of Migraine Chronification: a Pilot Study of 1911A>G Polymorphism of TRPV1 Gene in Episodic Versus Chronic Migraine, Journal of Molecular Neuroscience 71(3): 618 - 624, 2021.

40. M. Prakash, M. Abdelaziz, L. Zhang, B.A. Strange, and J. Tohka. Quantitative longitudinal predictions of Alzheimer's disease by multi-modal predictive learning. Journal of Alzheimer's Disease 79(4):1533-1546, 2021. [BioRxiv]

41. Valverde JM, Shatillo A, De Feo R, Gröhn O, Sierra A and Tohka J. RatLesNetv2: A Fully Convolutional Network for Rodent Brain Lesion Segmentation. Front. Neurosci. 14:1333, 2020. [arXiv: 2001.09138] (open access) [Software]

42. C. Sevilla Salcedo, V. Gomez-Verdejo, and J. Tohka.  Regularized Bagged Canonical Component Analysis for Multiclass Learning in Brain Imaging. Neuroinformatics 18, pages 641–659, 2020 [bioRxiv 698134]

43. H. Rostalski, T.  Hietanen, S. Leskelä, A. Behanova, A. Abdollahzadeh, R. Wittrahm, P. Mäkinen, N. Huber, D. Hoffmann, E. Solje, A.M.  Remes, T. Natunen, M. Takalo, J.  Tohka, M. Hiltunen and A. Haapasalo. BV-2 microglial cells overexpressing C9orf72 hexanucleotide repeat expansion produce DPR proteins and show normal functionality but no RNA foci.  Front. Neurol. | doi: 10.3389/fneur.2020.550140 , 2020 (open access) 

44. M. Kärkkäinen, M. Prakash, M. Zare, and J. Tohka. Structural brain imaging phenotypes of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) found by hierarchical clustering. International Journal of Alzheimer’s Disease, Article ID 2142854, 2020. (open access)

45. E. Manninen, K. Chary, N. Lapinlampi, P. Andrade, T. Paananen, A. Sierra Lopez, J. Tohka, O. Gröhn and A. Pitkänen. Early increase in cortical T2 relaxation is a prognostic biomarker for the evolution of severe cortical damage, but not for epileptogenesis, after experimental traumatic brain injury, Journal of Neurotrauma 37:2580 - 2594, 2020, in press. (open-access) 

46.  I. San Martin Molina, R.A. Salo, A. Abdollahzadeh, J. Tohka, O. Gröhn and A. Sierra. In vivo diffusion tensor imaging in acute and subacute phases of mild traumatic brain injury in rats. eNeuro, 7 (3) ENEURO.0476-19.2020. 

47. N. Vuokila, S. Das Gupta, R. Huusko, J. Tohka, N. Puhakka, and A. Pitkänen, Elevated acute plasma miR-124-3p level relates to evolution of larger cortical lesion area after traumatic brain injury. Neuroscience 433, pages 21 - 35, 2020

48. Shisei Tei, Jukka-Pekka Kauppi, Kathryn F. Jankowski, Junya Fujino, Ricardo P. Monti, Jussi Tohka, Nobuhito Abe, Toshiya Murai, Hidehiko Takahashi, Riitta Hari. Brain and behavioral alterations in subjects with social anxiety dominated by empathic embarrassment.  Proceedings of the National Academy of Sciences Feb 2020, 201918081 (open-access)

49. M. Fratini, A. Abdollahzadeh, M. DiNuzzo, R.A.  Salo,  L.  Maugeri, A. Cedola, F. Giove, O. Gröhn, J. Tohka,  and A.  Sierra.  Multiscale Imaging Approach for Studying the Central Nervous System: Methodology and Perspective. Frontiers in Neuroscience 14:72, 2020 (open access)

50. Aino I.L. Saarinen, Sanna Huhtaniska, Juho Pudas, Lassi Björnholm, Tuomas Jukuri, Jussi Tohka, Niklas Granö, Jennifer H. Barnett, Vesa Kiviniemi, Juha Veijola, Mirka Hintsanen, Johannes Lieslehto. Structural and functional alterations in the brain gray matter among first-degree relatives of schizophrenia patients: A multimodal meta-analysis of fMRI and VBM studies, Schizophrenia Research, 216: 14 - 23. 2020. 

51. J. Salmi, M. Metwaly; J. Tohka; K. Alho; S. Leppämäki; P. Tani; A. Koski; T. Vanderwal; M. Laine. ADHD desynchronizes brain activity during watching a distracted multi-talker conversation. NeuroImage 216: 116352 , 2020. (open access)

52. A. Lipponen, T. Natunen, M. Hujo, R. Ciszek, E. Hämäläinen, J. Tohka, M. Hiltunen, J. Paananen, D. Poulsen, E. Kansanen, X. Ekolle Ndode-Ekane, A.-L. Levonen, A. Pitkänen. In vitro and in vivo pipeline for validation of disease-modifying effects of systems biology-derived network treatments for traumatic brain injury – lessons learned. International Journal of Molecular Sciences 20(21), 5395, 2019.

53. J. Tiihonen, M. Koskuvi, M. Storvik, I. Hyötyläinen, Y. Gao, K.A. Puttonen, R. Giniatullina, E. Poguzhelskaya, I. Ojansuu, O. Vaurio, T.D. Cannon, J. Lönnqvist, S. Therman, J. Suvisaari, J. Kaprio, L. Cheng, A.F. Hill, M. Lähteenvuo, J. Tohka, R. Giniatullin, Š. Lehtonen  and J. Koistinaho.  Sex-specific transcriptional and proteomic signatures in schizophrenia. Nature Communications, vol. 10, Article number: 3933 , 2019 (open-access).

54. S. S. Hassan, H. Huttunen, J. Niemi, J. Tohka. Bayesian Receiver Operating Characteristic Metric for Linear Classifiers.  Pattern Recognition Letters 128:52 - 59, 2019. [arXiv preprint]

55. Pablo M. Casillas-Espinosa, Pedro Andrade, Cesar Santana-Gomez, Tomi Paananen, Gregory Smith, Idrish Ali, Robert Ciszek, Xavier Ekolle Ndode-Ekane, Rhys D. Brady, Jussi Tohka, Matthew R. Hudson, Piero Perucca, Emma L. Braine, Riikka Immonen, Noora Puhakka, Sandy R. Shultz, Nigel C. Jones, Richard J. Staba, Asla Pitkänen, Terence J. O’Brien, Harmonization of the pipeline for seizure detection to phenotype post-traumatic epilepsy in a preclinical multicenter study on post-traumatic epileptogenesis, Epilepsy Research 156: 106 - 131, 2019

56. John D Lewis, Vladimir S Fonov, D Louis Collins, Alan C Evans, Jussi Tohka.  Cortical and subcortical T1 white/gray contrast, chronological age, and cognitive performance, NeuroImage, 196:276 -- 288, 2019 [BioRxiv preprint] 

57. A. Abdollahzadeh, I. Belevich, E. Jokitalo, J. Tohka*, A. Sierra*. Automated 3D Axonal Morphometry of White Matter.  Scientific Reports 9:6084, 2019, [bioRxiv preprint]; doi: https://doi.org/10.1101/239228 *joint senior authors 

58. V. Gomez-Verdejo, E. Parrado-Hernandez, J. Tohka. Sign-Consistency Based Variable Importance For Machine Learning In Brain Imaging. Neuroinformatics 17:593 - 609, 2019 (open access), [BioRxiv preprint]. 

59. R. Ciszek, X. Ekolle Ndode-Ekane, C. Santana Gomez, P. M. Casillas-Espinosa, I. Ali, G. Smith, N. Puhakka, N. Lapinlampi, P. Andrade, A. Kamnaksh, R. Immonen, T. Paananen, M.R. Hudson, R.D. Brady, S.R. Shultz, T.J. O’Brien, R. J. Staba, J. Tohka, A. Pitkänen.  Informatics tools to assess the success of procedural harmonization in preclinical multicenter biomarker discovery study on post-traumatic epileptogenesis. Epilepsy Research 150: 17 - 26, 2019.

60. S. Huhtaniska, I. Korkala, T. Heikka, L. Björnholm, H. Lehtiniemi, A. Hulkko, J. Moilanen, J. Tohka , J.V. Manjon, P. Coupe, V. Kiviniemi, M. Isohanni, H. Koponen, G. Murray, J. Miettunen, E. Jääskeläinen. Antipsychotic and benzodiazepine use and brain morphology in schizophrenia and affective psychoses – systematic reviews and birth cohort study. Psychiatry Research: Neuroimaging ,281: 43 - 52, 2018.

61. J.D. Lewis, A.C- Evans, J. Tohka . T1 white/gray contrast as a predictor of chronological age, and an index of cognitive performance. NeuroImage 173:341 - 350, 2018 [BioRxiv preprint]

62. M. Gomez-Sancho, J. Tohka* , V. Gomez-Verdejo*. Comparison of feature representations in MRI-based MCI-to-AD conversion prediction. Magnetic Resonance Imaging, 50:84 - 95, 2018.  [bioRxiv preprint 213132] * joint senior authors

63. S. Huhtaniska, E. Jääskeläinen, T. Heikka, J.S. Moilanen, H. Lehtiniemi, J. Tohka , J. V. Manjón, P. Coupé, L. Björnholm, H. Koponen, J. Veijola, M. Isohanni, V. Kiviniemi, G. K. Murray, J. Miettunen, Long-term antipsychotic and benzodiazepine use and brain volume changes in schizophrenia: The Northern Finland Birth Cohort 1966 study, Psychiatry Research: Neuroimaging, 266(30):73-82,2017

64. J.-P. Kauppi, J. Pajula, J.A. Niemi, R. Hari, J. Tohka : Functional brain segmentation using inter-subject correlation in fMRI. Human Brain Mapping, 38: 2643–2665 , 2017. [biorxiv preprint]

65. E. Moradi, I. Hallikainen, T.Hänninen, J. Tohka : Rey's Auditory Verbal Learning Test scores can be predicted from whole brain MRI in Alzheimer's disease. NeuroImage: Clinical 13, 415 - 427,  2017 (open access)

66. E. Moradi, B Khundrakpam, J. Lewis, A.C. Evans, J. Tohka : Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data, Neuroimage, 144 (Pt A), 128 - 141, 2017. [biorxiv preprint]

67. J. Tohka , P. Bellec, C. Grova, A. Reilhac. Editorial: Simulation and Validation in Brain Image Analysis. Computational Intelligence and Neuroscience. Article ID 1041058, 2016. (open access) 

68. J. Johansson, K. Alakurtti, J. Joutsa, J. Tohka , U. Ruotsalainen, J.O. Rinne. Comparison of manual and automatic techniques for substriatal segmentation in 11C-raclopride high-resolution PET studies. Nuclear Medicine Communications 37(10), 1074 - 1087, 2016.

69. I.P Jääskeläinen*, J. Pajula*, J. Tohka* , H-J Lee, W-J Kuo, F-H. Lin .Brain hemodynamic activity during viewing and re-viewing of comedy movies explained by experienced humor. Scientific Reports 6, , article number 27741, 2016 (open access). * Equal contribution

70. J. Tohka , E. Moradi, and H. Huttunen. Comparison of feature selection techniques in machine learning for anatomical brain MRI in dementia. Neuroinfomatics ,14(3):279 - 296, 2016 . [Preprint] . The final publication is available at Springer at here .

71. J. Pajula and J. Tohka . How Many is Enough? Effect of Sample Size in Inter-Subject Correlation Analysis of fMRI. Computational Intelligence and Neuroscience, articleID 2094601, 2016. (open access)

72. Matthew Reason, Dee Reynolds, Rosie Kay, Corinne Jola, Jukka-Pekka Kauppi, Marie-Helene Grobras, Jussi Tohka , Frank E. Pollick. Spectators' Aesthetic Experience of Sound and Movement in Dance Performance: A Transdisciplinary Investigation, Psychology of Aesthetics, Creativity, and the Arts Vol 10(1):42 - 55, Feb 2016. [Preprint] [ISC software]

73. H. Huttunen, and J. Tohka . Model Selection for Linear Classifiers using Bayesian Error Estimation. Pattern Recognition , 48(11): 3739 - 3748, 2015. [Preprint]

74. Aleksandra Herbec, Jukka-Pekka Kauppi, Corinne Jola, Jussi Tohka , Frank E. Pollick. Differences in fMRI intersubject correlation while viewing unedited and edited videos of dance performance. Cortex , 71:341 - 348, 2015 . [Preprint] [ISC Software]

75. Khundrakpam BS*, Tohka J*, Evans AC. Prediction of brain maturity based on cortical thickness at different spatial resolutions. NeuroImage, 111:350-359, 2015. [Paper]

    1. * Equal contribution

76. Romero JE, Manjón JV, Tohka J , Coupé P, Robles M. NABS: non-local automatic brain hemisphere segmentation. Magnetic Resonanace Imaging, 33(4): 474 - 484, 2015 . [Paper]

77. Bron EE, Smits M, van der Flier WM, Vrenken H, Barkhof F, Scheltens P, Papma JM, Steketee RM, Orellana CM, Meijboom R, Pinto M, Meireles JR, Garrett C, Bastos-Leite AJ, Abdulkadir A, Ronneberger O, Amoroso N, Bellotti R, Cárdenas-Peña D, Álvarez-Meza AM, Dolph CV, Iftekharuddin KM, Eskildsen SF, Coupé P, Fonov VS, Franke K, Gaser C, Ledig C, Guerrero R, Tong T, Gray KR, Moradi E, Tohka J , Routier A, Durrleman S, Sarica A, Di Fatta G, Sensi F, Chincarini A, Smith GM, Stoyanov ZV, Sørensen L, Nielsen M, Tangaro S, Inglese P, Wachinger C, Reuter M, van Swieten JC, Niessen WJ, Klein S; for the Alzheimer's Disease Neuroimaging Initiative. Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge. NeuroImage , 11: 562 - 579, 2015. [Pubmed Central]

78. J. Tohka . Rigid body registration. In Brain Mapping: An Encyclopedic Reference , Volume 1, pages 301 - 305, 2015.

79. E. Moradi, A. Pepe, C. Gaser, H. Huttunen, and J. Tohka . Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects. NeuroImage , 104: 398 - 412, 2015. [MCI progressive/stable labels] [Preprint]

80. J. Tohka. Partial volume effect modeling for segmentation and tissue classification of brain magnetic resonance images: A review. World Journal of Radiology , 6(11): 855 - 864, 2014. (open-access) [Pubmed Central]

81. A. Foi, M. Maggioni, A. Pepe, S. Rueda, J.A. Noble, A. T. Papageorghiou, and J. Tohka . Difference of Gaussians Revolved Along Elliptical Paths for Ultrasound Fetal Head Segmentation. Computerized Medical Imaging and Graphics , 38(8): 774 - 784, 2014 . [Software (Matlab)] [Preprint]

82. J. Pajula and J. Tohka . Effects of Spatial Smoothing on Inter-Subject Correlation Based Analysis of FMRI. Magnetic Resonance Imaging 32(9): 1114 - 1124,, 2014 . [Preprint]

83. A. Pepe, I. Dinov, and J. Tohka . An Automatic Framework for Quantitative Validation of Voxel Based Morphometry Measures of Anatomical Brain Asymmetry. NeuroImage , 100: 444 - 459, 2014 . [Pubmed Central version]

84. J.-P. Kauppi, J. Pajula and J. Tohka . A Versatile Software Package for Inter-subject Correlation Based Analyses of fMRI. Frontiers in Neuroinformatics, 8:2, 2014. (open-access) [Software]

85. S. Rueda, S. Fathima, C.L. Knight, M. Yaqub, A. T. Papageorghiou, B. Rahmatullah, A. Foi, M. Maggioni, A. Pepe, J. Tohka , R.V. Stebbing, J.E. McManigle, A. Ciurte, X. Bresson, M. Bach Cuadra, C. Sun, G. V. Ponomarev, M. S. Gelfand, M. D. Kazanov, C.-W. Wang, H.-C. Chen, C.-W. Peng, C.-M. Hung, and J.A. Noble. Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge. IEEE Transactions on Medical Imaging 33(4):797 - 813, 2014

86. A. Pepe, L. Zhao, J. Koikkalainen, J. Hietala, U. Ruotsalainen and J. Tohka . Automatic statistical shape analysis of cerebral asymmetry in 3D T1-weighted magnetic resonance images at vertex-level: application to neuroleptic-naive schizophrenia, Magnetic Resonance Imaging , 31(5): 676 -- 87, 2013 .

87. H. Huttunen, T. Manninen, J.-P. Kauppi and J. Tohka . Mind Reading with Regularized Multinomial Logistic Regression. Machine Vision and Applications 24(6): 1311-1325, 2013. [Preprint]

88. J. Tohka and U. Ruotsalainen. Imaging brain change across different time scales. Front. Neuroinform. 6:29. doi: 10.3389/fninf.2012.00029 ,2012. (open-access)

89. J. Pajula, J.-P. Kauppi, and J. Tohka . Inter-Subject Correlation in fMRI: Method Validation against Stimulus-model Based Analysis, PLoS ONE, 7(8):e41196 2012. (open-access)

90. J. Tohka, Y. He and A.C. Evans. The impact of sampling density upon cortical network analysis: regions or points. Magnetic Resonance Imaging, 30(7):978 -992, 2012. [Corrigendum to Eq. (3)] [Postprint]

91. J.V. Manjon, J. Tohka , and M. Robles. Improved estimates of partial volume coefficients from noisy brain MRI using spatial context. NeuroImage,53(2):480-490, 2010. [Software (Matlab)]

92. J.-P. Kauppi, I.P. Jääskeläinen, M. Sams and J. Tohka . Inter-subject correlation of brain hemodynamic responses during watching a movie: localization in space and frequency, Frontiers in Neuroinformatics, 4:5. doi:10.3389/fninf.2010.00005 (open access) 2010 [Software (Matlab)]

93. L. Zhao, U. Ruotsalainen, J. Hirvonen, J. Hietala and J. Tohka . Automatic cerebral and cerebellar hemisphere segmentation in 3D MRI: adaptive disconnection algorithm. Medical Image Analysis , 14(3): 360 - 372, 2010 . [Software]

94. J. Tohka , I.D. Dinov, D.W. Shattuck, and A.W. Toga. Brain MRI Tissue Classification Based on Local Markov Random Fields, Magnetic Resonance Imaging , 28(4): 557 - 573, , 2010. [Postprint]

95. R.J. Farinha, U. Ruotsalainen, J. Hirvonen, L. Tuominen, J. Hietala, J.M. Fonseca, and J. Tohka . Segmentation of Striatal Brain Structures from High Resolution PET Images, International Journal of Biomedical Imaging vol. 2009, Article ID 156234, 12 pages, doi:10.1155/2009/156234, 2009. (open access)

96. E. Krestyannikov, J. Tohka and U. Ruotsalainen. Joint penalized-likelihood reconstruction of time activity curves and regions-of-interest from projection data in brain PET. Physics in Medicine and Biology, 53:2877-2896, 2008.

97. J. Tohka and A. Reilhac. Deconvolution-Based Partial Volume Correction in Raclopride-PET and Monte Carlo Comparison to MR Based Method. NeuroImage, 39(4):1570-1584, 2008. [Postprint]

98. J.V. Manjón, J. Tohka , G. García-Martí, J. Carbonell-Caballero, J.J. Lull, L. Martí-Bonmatí and M. Robles. Robust MRI Brain Tissue Parameter Estimation by Multistage Outlier Rejection. Magnetic Resonance in Medicine, 59:866 - 873, 2008.

99. J. Tohka , K. Foerde, A.R. Aron, S. M. Tom, A.W. Toga, and R.A. Poldrack. Automatic Independent Component Labeling for Artifact Removal in fMRI. NeuroImage, 39(3):1227-45, 2008. [Software] [Pubmed Central version]

100. E. Wallius, J. Tohka , J. Hirvonen, J. Hietala, and U. Ruotsalainen. Evaluation of the automatic three-dimensional delineation of caudate and putamen for PET receptor occupancy studies. Nuclear Medicine Communications , 29(1):53-65, 2008.

101. J. Tohka , E. Krestyannikov, I.D. Dinov , A. MacKenzie-Graham, D.W. Shattuck , U. Ruotsalainen, and A.W. Toga. Genetic algorithms for finite mixture model based voxel classification in neuroimaging. IEEE Transactions on Medical Imaging , 26(5):696 - 711, 2007. [Software (Matlab)] [Software (C/C++)]

102. D. Glotsos, J. Tohka , J. Soukka, J. Soini, and U. Ruotsalainen. Robust estimation of bioaffinity assay fluorescence signals. IEEE Transactions on Information Technology in Biomedicine , 10(4):733- 739 Oct. 2006

103. J. Tohka , E. Wallius, J. Hirvonen, J. Hietala, and U. Ruotsalainen. Automatic extraction of caudate and putamen in [11C]raclopride PET using deformable surface models and normalized cuts. IEEE Transactions on Nuclear Science , 53(1):220-227 , 2006. [Postprint]

104. A. Reilhac, G. Batan, C. Michel, C. Grova, J. Tohka , D.L. Collins, N. Costes, and A.C. Evans. PET-SORTEO: Validation and development of database of simulated PET volumes. IEEE Transactions on Nuclear Science , 52(5): 1321-1328 , 2005. [Database]

105. J. Mykkänen, J. Tohka, J. Luoma, and U. Ruotsalainen. Automatic extraction of brain surface and mid-sagittal plane from PET images applying deformable models. Computer Methods and Programs in BioMedicine,17(1):1 - 17 , 2005. [See the related technical report]

106. D. Glotsos, J. Tohka , P. Ravazoula, D. Cavouras, and G. Nikiforidis. Automated Diagnosis of Brain Tumours Astrocytomas Using Probabilistic Neural Network Clustering and Support Vector Machines, International Journal of Neural Systems , 15(1 -2):1 - 12, 2005 [Full text via EBSCO database]

107. J. Tohka. Global deformable surface optimization using adaptive constraints and penalties. Image Analysis and Stereology, 24:9 - 19, 2005. [Preprint]

108. J. Tohka, A. Kivimäki, A. Reilhac, J. Mykkänen, and U. Ruotsalainen.  Assessment of brain surface extraction from PET images using Monte Carlo simulations.IEEE Transactions on Nuclear Science,51(5):2641 - 2648, 2004.

109. J. Tohka, A. Zijdenbos, and A.C. Evans. Fast and robust parameter estimation for statistical partial volume models in brain MRI. NeuroImage, 23(1):84 - 97, 2004. [Software (Matlab)] [Postprint]

110. J. Tohka, J. Mykkänen. Deformable mesh for automated surface extraction from noisy images. International Journal of Image and Graphics, Special Issue on Deformable Models for Image Analysis and Pattern Recognition 4(3):405-432, July 2004 . [preprint]. [Software]

111. J. Mykkänen, J. Tohka, and U. Ruotsalainen. Automated delineation of brain structures with snakes in PET. in Molecular and Pharmacological Brain Imaging with Positron Emission Tomography,  pages 39-43. Academic Press, 2001.

Refereed articles in international conferences (review based on full-paper):

In image analysis and pattern recognition, certain conferences are very selective and well regarded (equaling the best specialist journals) publication venues. For example, conferences such as MICCAI or ECCV accept under 30% of papers. All the conference papers in this section have received a proper peer review based on full paper and typically the acceptance rate has been under 50 %.

1. Vandad Imani, Elaheh Moradi, Carlos Sevilla-Salcedo, Vittorio Fortino, Jussi Tohka. Optimizing Feature Selection for Binary Classification with Noisy Labels: A Genetic Algorithm Approach. Accepted to International Conference on Advances in Computing Research 2024, Springer. 

2. Mohammad Khateri, Morteza Ghahremani, Alejandra Sierra, Jussi Tohka. Self-Supervised Super-Resolution Approach for Isotropic Reconstruction of 3D Electron Microscopy Images from Anisotropic Acquisition,11th European Workshop on Visual Information Processing (EUVIP), IEEE, 2023. [arXiv] 

3. Juan Miguel Valverde, Artem Shatillo, Riccardo de Feo, Olli Gröhn, Alejandra Sierra, Jussi Tohka. Automatic Rodent Brain MRI Lesion Segmentation with Fully Convolutional Networks. Machine Learning in Medical Imaging, Lecture Notes in Computer Science 2019. [arXiv]

4. J.M. Valverde, V. Imani, J.D. Lewis, J. Tohka,  Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry.  ABCD Neurocognitive Prediction Challenge, Lecture Notes in Computer Science, 2019.

5. V. Gomez-Verdojo, E. Parrado-Hernandez, J. Tohka . Voxel importance in classifier ensembles based on sign consistency patterns: Application to sMRI. IEEE International workshop on Pattern Recognition in Neuroimaging 2016. [Paper].

6. E. Moradi, C. Gaser, H. Huttunen, J. Tohka . MRI based dementia classification using semi-supervised learning and domain adaptation. In: Proc MICCAI workshop Challenge on Computer-Aided Diagnosis of Dementia Based on Structural MRI Data. 2014. p. 65–73. [Paper]

7. E. Moradi, C. Gaser, and J. Tohka . Semi-supervised learning in MCI-to-AD conversion prediction - When is unlabeled data useful?. IEEE International workshop on Pattern Recognition in Neuroimaging 2014, pp. 121 - 124 . [Paper].

8. H. Huttunen, T. Manninen, and J. Tohka . Bayesian Error Estimation And Model Selection In Sparse Logistic Regression. IEEE Machine Learning for Signal Processing Workshop, pp. 1 - 6, 2013 . [See the journal paper instead]

9. J. Tohka . FAST-PVE: Extremely Fast Markov Random Field Based Brain MRI Tissue Classification. SCIA 2013, Scandinavian Conference on Image Analysis, Helsinki, Finland, 2013, Lecture Notes in Computer Science vol 7944 pp. 266 - 276, 2013. [Preprint].

10. *A. Pepe, *L. Brandolini, M. Piastra, J. Koikkalainen, J. Hietala and J. Tohka . Simplified Reeb Graph as Effective Shape Descriptor for the Striatum In, R.R. Paulsen and J.A. Levine, editors, MICCAI 2012 Mesh Processing in Medical Image Analysis, Lecture Notes in Computer Science 7599, pp. 134 - 146 , Nice, France, 2012. * Equal contribution [Paper]

11. A. Pepe and J. Tohka. 3D bending of surfaces and volumes with an application to brain torque modeling. In 1st International Conference of Pattern Recognition Applications and Methods, pp. 411 - 418, Algarve, Portugal, 2012. [Paper]

12. H. Huttunen, T. Manninen, and J. Tohka. Mind reading with multinomial logistic regression: Strategies for feature selection, Federated Computer Science Event pp. 42 - 49, Helsinki, Finland, 2012 . [Paper]

13. A. Foi, M. Maggioni, A. Pepe and J. Tohka. Head contour extraction from fetal ultrasound images by difference of Gaussians revolved along elliptical paths. Proceedings of Challenge US: Biometric Measurements from Fetal Ultrasound Images ISBI 2012, pp. 1 - 3, 2012 

14. A. Pepe, L. Zhao, J. Tohka , J. Koikkalainen, J. Hietala, and U. Ruotsalainen. Automatic Statistical Shape Analysis of Local Cerebral Asymmetry in 3D T1-weighted magnetic resonance images. In, R.R. Paulsen and J.A. Levine, editors, Proc. of MICCAI 2011 MedMesh workshop, Toronto, Canada, pp. 127 - 134, 2011

15. J.-P. Kauppi, H. Huttunen, H. Korkala, I.P. Jääskeläinen, M. Sams, and J. Tohka . Face Prediction from fMRI Data during Movie Stimulus: Strategies for Feature Selection. In Artificial Neural Networks and Machine Learning - ICANN 2011, Lecture Notes in Computer Science vol. 6792, pp. 189 - 196 , 2011. [Postprint]

16. J.-P. Kauppi, I.P. Jääskeläinen, M. Sams, and J. Tohka . Clustering Inter-Subject Correlation Matrices in Functional Magnetic Resonance Imaging. Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB10), pages 1 - 6, Corfu, Greece, November 3-5, 2010. [Postprint]

17. L. Zhao, J. Hietala and J. Tohka . Shape analysis of human brain interhemispheric fissure bending in MRI. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, Lecture Notes in Computer Science vol. 5762, pp. 216 - 223, London, UK, 2009. [Postprint]

18. H. Pölönen, J. Tohka and U. Ruotsalainen. Automatic Intensity Quantification of Fluorescence Targets from Microscope Images with Maximum Likelihood Estimation. In Proc. of European Signal Processing Conference (EUSIPCO-2009), pp. 1072 - 1076, Glasgow, UK, 2009. [Paper]

19. H. Pölönen, J. Tohka and U. Ruotsalainen. Automatic Quantification of Fluorescence from Clustered Targets in Microscope Images. Lecture Notes in Computer Science vol. 5575 (Proc. of Scandinavian Conference on Image Analysis (SCIA09)), pp. 667 - 675, Oslo, Norway, 2009.

20. L. Zhao, J. Tohka . Automatic compartmental decomposition for 3D MR images of human brain. In Proc. of 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ,pp. 3888-3891 ,Vancouver, Canada, 2008. [Paper]

21. L. Zhao, J. Tohka , U. Ruotsalainen. Accurate 3D left-right brain hemisphere segmentation in MR images based on shape bottlenecks and partial volume estimation. In Scandinavian Conference on Image Analysis, Aalborg, Denmark, June 10-14,Lecture Notes in Computer Science 4522 , pages 581 - 590 , Springer Verlag, 2007. [Paper]

22. H. Pölönen, M. Jansen, J. Tohka , E. Ikonen, U. Ruotsalainen: Automatic method for caveolar structure detection and intensity distribution analysis from microscopy images, In Proc. of European Signal Processing Conference (EUSIPCO 2007) , Poznan, Poland, September 3 - 7, pp. 1107 - 1111, 2007. [Paper]

23. E. Krestyannikov, J. Tohka , U. Ruotsalainen. Statistical modeling of attenuation corrected data in PET with application to reconstruction of regional time activity curves. In IEEE International Symposium on Biomedical Imaging (IEEE-ISBI), Washington D.C., US, 12-15 April, 2007, pages 444 - 447 . [Preprint]

24. E. Krestyannikov, J. Tohka, U. Ruotsalainen. Segmentation of dynamic emission tomography data in projection space. In Computer Vision Approaches to Medical Image Analysis (CVAMIA) Workshop, Graz Austria, Lecture Notes in Computer Science vol. 4241 , pp. 108 - 119, 2006.

25. A. Juslin, J. Tohka . Unsupervised segmentation of cardiac PET transmission images for automatic heart volume extraction. In Proc. of IEEE 2006 International Conference of the Engineering in Medicine and Biology Society (EMBC06) , pp. 1077 - 1080 , August 30-September 3 2006, New York, USA. [Software] [Paper]

26. J. Mykkänen, J. Itäranta, J. Tohka. Object oriented implementation for the dual surface minimisation algorithm. In Connecting Medical Informatics and Bio-Informatics, Proceedings of MIE2005, volume 116 of Studies in Health Technology and Informatics, , pp. 477 - 482. IOS-Press. Geneva, Switzerland, 2005. [Software]

27. A. Juslin, A. Reilhac, M. Magadan-Mendez, E. Alban, J. Tohka, and U. Ruotsalainen. Assessment of separation of functional components with ICA from cardiac perfusion PET phantom images for volume extraction with deformable surface model. In Proc of 3rd Int. Conf. on Functional Imaging and Modeling of the Heart (FIMH'05), Lecture Notes in Computer Science 3504, pp. 338 - 347, Barcelona, Spain, June 2005.

28. J. Tohka. Surface Smoothing Based on a Sphere Shape Model. In Proc. of 6th Nordic Signal Processing Symposium, NORSIG2004, pp. 17 - 20, Espoo, Finland, June, 2004.  [Link to proceedings]

29. H. Koivistoinen, J.Tohka, and U. Ruotsalainen. Comparison of Pattern Classification Methods in Segmentation of Dynamic PET Brain Images. In Proc. of 6th Nordic Signal Processing Symposium, NORSIG2004, pp. 73 - 76, Espoo, Finland, June, 2004. [Link to proceedings]

30. D.Glotsos, J. Tohka, J. Soukka, and U. Ruotsalainen. A new approach to robust clustering by density estimation in an autocorrelation derived feature space. In Proc. of 6th Nordic Signal Processing Symposium, NORSIG2004, pp. 296 - 299, Espoo, Finland,June, 2004.[Link to proceedings]

31. J. Mykkänen, J. Tohka, and U. Ruotsalainen. Delineation of brain structures from positron emission tomography images with deformable models.In the new navigators: from professionals to patients, Studies in Health Technology and Informatics volume 95, Proc. of Medical Informatics Europe,  pp. 33 - 38, IOS-Press, St. Malo, France, June,  2003. [Paper]

32. J. Tohka. Surface extraction from volumetric images using deformable meshes: A comparative study. in Proc. of 7th European Conference on Computer Vision, Lecture Notes in Computer Science 2352 , pp. 350 - 364,  Springer-Verlag,Copenhagen, Denmark, May 2002. [Paper][Abstract]

33. U. Ruotsalainen, J. Mykkänen, J. Luoma, J. Tohka, and S. Alenius. Methods to improve repeatability in quantification of brain PET images. In World Congress on Neuroinformatics: Part II Proceedings, ARGESIMReport no. 20, pages 659 – 664. Agresim-Verlag, 2001.

34. J. Tohka. Global optimization of deformable surface meshes based on genetic algorithms. in Proc. of 11th International Conference of Image Analysis and Processing, pp. 459 - 464, IEEE CS Press, Palermo, Italy, September 2001. [Paper][Abstract]

Other full-length international conference papers (review based on abstract or few page summary):

1. H. Huttunen, J-P. Kauppi, and J. Tohka. Regularized logistic regression for mind reading with parallel validation," winning submission to ICANN2011 MEG challenge, p. 20-24, July 2011.

2. U. Tuna, J. Tohka , R. Farinha and U. Ruotsalainen. Evaluation of Automatic Striatal Segmentation for the ECAT HRRT Images. IEEE Nuclear Science Symposium & Medical Imaging Conference (MIC2010), in press, Knoxville, USA, October 30-November 6, 2010.

3. F. Momey, N. Boussion, D. Visvikis, J. Nuyts, N. Costes, J. Tohka and A. Reilhac. Evaluation of Deconvolution-Based Methods for the Correction of Partial Volume Effect in PET. In Proc. of IEEE Medical Imaging Conference, Dresden, Germany, in press, 2008.

4. L. Zhao, J. Tohka, J. Hirvonen, J. Hietala, and U. Ruotsalainen. Evaluation for a novel brain hemisphere segmentation method using MR images of schizophrenics and healthy controls. In proc. of Finnish Signal Processing Symposium (FINSIG'07), Oulu, Finland, ISBN 978-951-42-8546-2, 2007.

5. E. Wallius, J. Tohka , J. Hirvonen, J. Hietala, U. Ruotsalainen U. A method for automatic extraction of striatal structures for dose-finding studies in PET. In Proc of IEEE Medical Imaging Conference (MIC2006) , pp. 3189 - 3194, October 29-November 4, San Diego, California, USA, 2006.

6. A. Juslin, J. Tohka , J. Lötjönen, U. Ruotsalainen. Comparison of image segmentation and registration based methods for analysis of misaligned dynamic H2-O-15 cardiac PET images. In Proc . of IEEE Medical Imaging Conference (MIC2006) , pp. 3200 - 3204, October 29-November 4 2006, San Diego, California, USA, 2006.

7. J. Tohka , A. Reilhac. A Monte Carlo study of deconvolution algorithms for partial volume correction in quantitative PET. In Proc. of IEEE Medical Imaging Conference (MIC2006) , pp. 3339 - 3345, October 29-November 4, San Diego, California, USA, 2006.[Erratum]

8. J. Tohka, E. Krestyannikov, I. Dinov, D. Shattuck, U. Ruotsalainen, A.W. Toga. Genetic algorithms for finite mixture model based tissue classification in brain MRI. In Proc. of European Medical and Biological Engineering Conference, IFMBE Proceedings vol. 11, pp. 4077 - 4082, Prague, Czech Republic, 2005. [Paper] [Software]

9. E. Alban, J. Tohka, and U. Ruotsalainen. Adaptive Edge Detection Based on 3D Kernel Functions for Biomedical Image Analysis. In SPIE Electronic Imaging, Image Processing: Algorithms and Systems IV, Proc.SPIE 5672 , pp.224 - 235, San Jose, CA, USA, January 2005.

10. G. Batan, A. Reilhac, C. Grova, D.L. Collins, J. Tohka, N. Costes, and A. Evans. A database of simulated PET volumes with anatomical variability. In Proc. of IEEE Medical Imaging Conference (MIC2004) , pp. 3699 - 3702, Rome, Italy, October 2004.

11. J. Tohka, E. Wallius, J. Hirvonen, J. Hietala, and U. Ruotsalainen. Improved Reproducibility in Dopamine D2-Receptor Studies with Automatic Segmentation of Striatum from PET Images, In Proc of IEEE Medical Imaging Conference (MIC2004), pp. 2690 - 2694, Rome, Italy, October 2004.[Paper]

12. D. Glotsos, J. Tohka, J.Soukka, J. Soini, and U. Ruotsalainen.A New Robust Clustering Method for the Automatic Identification of Different Types of Analytes in Multi-Parametric Bioaffinity Assays, In Proc. of the 4th European Symposium on Biomedical Engineering, 25-27 June 2004, Patras, Greece, paper S4.03 (4 pages).

13. D. Glotsos, J. Tohka, J. Soukka, J. Soini, and U. Ruotsalainen. A New Method for Concentration Estimation in Multiparametric Bioaffinity Immunoassays, In Proc. of the 4th European Symposium on Biomedical Engineering, 25-27 June 2004, Patras, Greece, paper S4.02 (4 pages).

14. J. Tohka, A. Kivimäki, A. Reilhac, J. Mykkänen, U. Ruotsalainen. Brain surface extraction from PET images using deformable models: Assessment using Monte-Carlo simulator, In Proc. of IEEE Medical Imaging Conference (MIC2003), pp. 3115 - 3119, Portland, Oregon, USA, October, 2003. [Errata]

15. J. Tohka. Note on connections between active contours and Rayleigh quotients.In Proceedings of 2001 Finnish Signal Processing Symposium, pp. 59 - 62, Espoo, Finland, June 2001.  [Paper]

16. U. Ruotsalainen, J. Mykkänen, J. Luoma, J. Tohka and S. Alenius. Methods to improve repeatability in quantification of brain PET images, In World Congress on Neuroinformatics, AGRESIM Reprort no. 20, pp. 659 - 664, Agresim-Verlag, Vienna, Austria, September 2001. [Abstract]

Refereed international conference abstracts (only until 2016):

1. S Huhtaniska, I Korkala, T Heikka, J Tohka, J Manjon, P Coupe, J Remes, J Moilanen, V Kiviniemi, L Björnholm, M Isohanni, J Veijola, G Murray, E Jääskeläinen, J Miettunen. Lifetime antipsychotic use and brain structures in schizophrenia and other psychoses–43-year study of the Northern Finland Birth Cohort 1966 European Psychiatry 33: S102 - 103, 2016.

2. Jussi Tohka, Elaheh Moradi, Heikki Huttunen. Feature selection stability in machine learning with anatomical brain MRI. 22nd Annual Meeting of the Organisation for Human Brain Mapping, Geneva, Switzerland, 2016.

3. Jussi Tohka, Elaheh Moradi, Heikki Huttunen. Bayesian error estimation for model selection in machine learning for brain imaging. 22nd Annual Meeting of the Organisation for Human Brain Mapping, Geneva, Switzerland, 2016.

4. Antonietta Pepe, Hamed Rabiei, Jussi Tohka, Ivo Dinov, Julien Lefèvre. Modelling Growth and Tangential Expansion in the Brain Surface. A Practical Framework. 22nd Annual Meeting of the Organisation for Human Brain Mapping, Geneva, Switzerland, 2016.

5. Juha Pajula, Jukka-Pekka Kauppi, Jussi Tohka. Functional Segmentation of Brain fMRI Based on Inter-Subject Correlation. 21st Annual Meeting of the Organisation for Human Brain Mapping, Honolulu, USA, 2015.

6. B Khundrakpam, J Lewis, J Tohka, A Evans. Dissociating Autistic from Normal Brains Based on Prediction of Biological Maturity. Biological Psychiatry 17(9) 229S, 2014

7. Jussi Tohka, Juha Pajula, Iiro Jääskeläinen, Wen-Jui Kuo, Fa-Hsuan Lin. FMRI inter-subject correlations during viewing of comedy movies explained by experienced humor. 20nd Annual Meeting of the Organisation for Human Brain Mapping, Hamburg, Germany, 2014.

8. Frank Pollick, Marie-Helene Grosbras, Jukka-Pekka Kauppi, Jussi Tohka. Using Intersubject Correlation to compare brain activity across several audiovisual dance videos. 20nd Annual Meeting of the Organisation for Human Brain Mapping, Hamburg, Germany, 2014.

9. Elaheh Moradi, Christian Gaser, Antonietta Pepe, Heikki Huttunen, Jussi Tohka. Semi-supervised learning for early MRI-based MCI-to-AD conversion prediction. 20nd Annual Meeting of the Organisation for Human Brain Mapping, Hamburg, Germany, 2014

10. Antonietta Pepe, Ivo Dinov, Jussi Tohka. An Automatic Framework for Quantitative Validation of VBM Measures of Anatomical Brain Asymmetry.20nd Annual Meeting of the Organisation for Human Brain Mapping, Hamburg, Germany, 2014

11. Juha Pajula, Jukka-Pekka Kauppi, Jussi Tohka. A Versatile Software Package for Inter-subject Correlation Based Analyses of fMRI. 20nd Annual Meeting of the Organisation for Human Brain Mapping, Hamburg, Germany, 2014

12. Khundrakpam, B., Tohka, J., Evans, A.C. Structural MRI Predicts Biological Maturity, 2013 INCF Neuroinformatics Congress, Stockholm, Sweden.

13. J. Pajula, J. Tohka. Effects of Spatial Smoothing to Inter-Subject Correlation Based Analysis of fMRI, 19th Annual Meeting of the Organisation for Human Brain Mapping, Seattle, USA, 2013.

14. J. Pajula, J.-P. Kauppi, J. Tohka. Intersubject Correlation in fMRI: Method Validation Against General Linear Model, 18th Annual Meeting of the Organisation for Human Brain Mapping, Beijing, China, 2012.

15. J. Tohka, T. Manninen, J.-P. Kauppi and H. Huttunen. MEG Decoding with Regularized Multinomial Logistic Regression, 18th Annual Meeting of the Organisation for Human Brain Mapping, Beijing, China, 2012

16. Jukka-Pekka Kauppi, Iiro Jääskeläinen, Mikko Sams, Jussi Tohka, Inter-Subject Correlation Matrix Clustering in Naturalistic Stimulus fMRI, 17th Annual Meeting of the Organisation for Human Brain Mapping Quebec City, Canada, 2011.

17. L. Zhao, J. Tohka. ADisc - a pipeline for Adaptive Disconnection based brain hemisphere segmentation in 3D MRI,17th Annual Meeting of the Organisation for Human Brain Mapping Quebec City, Canada, 2011.

18. Pierre Bellec, Felix Carbonnell, Vincent Perlbarg, Claude Lepage, Oliver Lyttelton, Vladmir Fonov, Andrew Janke, Jussi Tohka, Alan Evans. A neuroimaging analysis kit for Matlab and Octave, 17th Annual Meeting of the Organisation for Human Brain Mapping Quebec City, Canada, 2011.

19. I. P. Jaaskelainen, J.-P. Kauppi, E. Glerean, J. Lahnakoski, J. Lampinen, J. Salmitaival, J. Tohka , M. Sams. Low-frequency inter-subject correlations of frontal pole hemodynamic activity during watching movies. Society for Neuroscience, San Diego, CA, USA, November, 2010.

20. P. Korkola, J. Tohka , M. O. Koskinen. Low-Noise Correction of Partial Volume Effect in whole body FDG-PET. EANM'10: Annual Congress of the European Association of Nuclear Medicine - October 9 - 13, 2010 - Austria, Vienna.

21. L. Zhao, J. Hietala, J. Tohka . Shape analysis for human brain Yakovlevian torque in MRI. 16th Annual Meeting of the Organisation of Human Brain Mapping, Barcelona, Spain, 2010.

22. J.-P. Kauppi, I. Jääskeläinen, M. Sams, J. Tohka . Permutation method to assess statistical significance in inter-subject correlations of fMRI signals. 16th Annual Meeting of the Organisation of Human Brain Mapping, Barcelona, Spain, 2010.

23. I.P. Jääskeläinen, J.-P. Kauppi, M. Sams, and J. Tohka. Inter-subject correlations in low-frequency prefrontal fMRI-BOLD activity during watching a movie Society for Neuroscience, Chicago, US, 2010.

24. J. P. Kauppi, I. Jaaskelainen, M. Sams and J. Tohka . A new software tool for analyzing BOLD fMRI during movie watching. Frontiers in Neuroinformatics. Conference Abstract: 2nd INCF Congress of Neuroinformatics. doi: 10.3389/conf.neuro.11.2009.08.032

25. A. Pepe, L. Zhao, J. Tohka ,J. Koikkalainen, J. Hietala and U. Ruotsalainen. Automatic statistical shape analysis of human cerebral asymmetry in 3D MRI. 15th Annual Meeting of the Organisation of Human Brain Mapping, San Francisco, June 18 - 23, 2009.

26. J.-P. Kauppi, I.P. Jääskeläinen, M. Sams and J. Tohka . Low-Frequency Specific Inter-subject Hemodynamic Synchronization in Frontal Cortex During Natural Vision. 15th Annual Meeting of the Organisation of Human Brain Mapping, San Francisco, June 18-23, 2009.

27. I.P. Jääskeläinen, J.-P. Kauppi, K. Koskentalo, J. Saramäki, J. Tohka and M. Sams. Use of naturalistic stimuli in disclosing brain dynamics. Frontiers in Human Neuroscience. Conference Abstract: Tuning the Brain for Music. doi: 10.3389/conf.neuro.09.2009.02.013

28. L. Zhao, U. Ruotsalainen, J. Hirvonen, J. Hietala and J. Tohka . Study of cerebral asymmetry in schizophrenia based on an novel automatic cerebral hemisphere segmentation method for MRI. Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2008.

29. A. Pepe, L. Zhao,J. Koikkalainen, J. Tohka , J. Hietala and U. Ruotsalainen. Automatic analysis of cerebral shape asymmetry in 3D MRI. Frontiers in Neuroinformatics. Conference Abstract: Neuroinformatics 2008.

30. J. Tohka , A. Reilhac. Deconvolution as an alternative to MR-based partial volume correction in Raclopride PET. Abstracts of the Turku PET Symposium, p. 48, 2008

31. J. Tohka , I.D. Dinov, D.W. Shattuck, and A.W. Toga. Brain MRI Segmentation Based on Local Markov Random Fields and Sub Volume Probabilistic Atlases. 14th Annual Meeting of the Organisation of Human Brain Mapping, Melbourne, Australia, 2008.

32. J. Tohka , I.D. Dinov, D.W. Shattuck, and A.W. Toga. GAMIXTURE+MRFSEG: A flexible tool for voxel classification. In proc. of Nordic Neuroinformatics Workshop, pp. 10, 2007.

33. L. Zhao, J. Tohka and U. Ruotsalainen. Automatic human brain hemisphere segmentation in MRI including brain compartmental decomposition. In proc. of Nordic Neuroinformatics workshop, pp. 36, 2007.

34. E. Wallius, J. Tohka , J. Hirvonen, J. Hietala, U. Ruotsalainen. Reduced standard deviation of binding potential values with automatic segmentation of striatum in PET - implications to statistical power. BrainPET'07 Conference, Osaka Japan, May 20-24, 2007.

35. L. Zhao, J. Tohka , U. Ruotsalainen. Accurate brain hemisphere segmentation in 3D MRI based on shape bottlenecks and partial volume estimation. 13th Annual meeting of Human Brain Mapping, Chicago, IL, USA, June 10-14, 2007.

36. J. Kunnari, J. Tohka . Comparison of three modified EM-algorithms in segmentation of dynamic PET images. 13th Annual meeting of Human Brain Mapping, Chicago, IL, USA, June 10-14, 2007.

37. J. Tohka , E. Wallius, J. Hirvonen, J. Hietala, U. Ruotsalainen. Partial volume effect, segmentation inaccuracy, and reproducibility in striatal D2 dopamine receptor availability with raclopride PET. Organization for Human Brain Mapping 2006, Florence, Italy, June 11-15, 2006.

38. J. Tohka , K. Foerde, A.W. Toga, R.A. Poldrack. Automatic independent component labeling for artifact reduction in fMRI. Organization for Human Brain Mapping, 2006, Florence, Italy, June 11-15, 2006.

39. K. Sederholm, J. Tohka , V. Oikonen, U. Ruotsalainen, S. Peltonen. Robust estimation of regional parameter values as a simple method for partial volume correction in PET imaging. Annales Universitatis Turkuensis D 660, X Turku PET Symposium: p. 82, 2005.

40. E. Wallius, J. Tohka , J. Hietala, U. Ruotsalainen. Automatic extraction of caudate and putamen from images during medication in [C-11]-raclopride PET. Annales Universitatis Turkuensis D 660, X Turku PET Symposium: p. 85, 2005.

41. A. Kivimäki, J. Tohka, M. Anttila, U. Ruotsalainen. Automatic extraction of the heart volumes from dynamic FDG PET emission images for movement corrections. In EANM'04 - Annual Congress of the European Assocation of Nuclear Medicine, European Journal of Nuclear Medicine and Molecular Imaging 31(Suppl. 2):S406, September 4 - 8, 2004 in Helsinki, Finland

42. A. Kivimäki, J. Tohka, U. Ruotsalainen. Monte Carlo Study of Automated MRI-PET Image Registration with Brain Images having pathological defects. In 2nd Nordic Neuroinformatics Workshop, Drobak, Norway, September, 2004.

43. J. Tohka, A. Zijdenbos, U. Ruotsalainen, A. Evans. Overview on partial volume estimation in brain MRI: Models and methods. 1st Nordic Workshop on Brain Imaging and Neuroinformatics, Tampere, Finland, 2003. [Abstract]

44. H. Koivistoinen, J. Tohka, U. Ruotsalainen.  Unsupervised learning methods in delineation of brain regions from PET images based on dynamic tracer distribution. 1st Nordic Workshop on Brain Imaging and Neuroinformatics, Tampere, Finland, 2003

45. J. Tohka. Target extraction from emission tomography images with deformable models. In  Workshop on Deformable Models, Gullmarstrand, Sweden, August 2000.

46. J. Mykkänen, J. Tohka, and U. Ruotsalainen. Automated delineation of brain structures with snakes in PET.XIX International Symposium on Cerebral Blood Flow, Metabolism and Function, IV International Conference on Quantification of Brain Function with PET, Cerebral Blood Flow and Metabolism 19(Suppl. 1):778, Copenhagen, Denmark, June 1999.

Lecture notes

1. J. Tohka. Introduction to Pattern Recognition, 74 pages, 2006 - 2012 [pdf] .

2. J. Tohka. Johdatus hahmontunnistukseen, 72 pages, 2006 - 2012 [pdf] .

Other:

1. J. Tohka.  Deformable surface meshes based on global optimization. Digest of TISE Seminar 2002, June 10, 2002, Ylöjärvi, Finland, pp. 7 -8, 2002.

2. J. Tohka. Automated surface extraction with deformable meshes. Online tutorial in CVonline. 2002.

3. J. Mykkänen, J. Tohka, J. Luoma, and U. Ruotsalainen. Automatic extraction of brain surface and mid-sagittal plane from PET images applying deformable models. Technical Report  A-2003-1, Department of  Computer and Information Sciences, University of Tampere, 2003. [Paper]

4. Pepe, Antonietta; Dinov, Ivo; Tohka, Jussi

   1. 1. An Automatic Neuroimaging Infrastructure For Synthesis and Analysis of Structural MRI Data