World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
5819
World Ranking
11623
National Ranking
100

Overview

Jussi Tohka is affiliated with the University of Eastern Finland in Finland and has contributed extensively to the field of medical research, particularly in the intersection of medicine and advanced imaging techniques. Their body of work encompasses a range of studies related to neuroimaging, neurology, psychiatry, and artificial intelligence as applied in healthcare.

Their recent notable publications include:

  • Evaluation of machine learning algorithms for health and wellness applications: A tutorial (2021) in Computers in Biology and Medicine
  • Transfer Learning in Magnetic Resonance Brain Imaging: A Systematic Review (2021) in Journal of Imaging
  • Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge (2021) in NeuroImage
  • The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up (2021) in The Journal of Machine Learning for Biomedical Imaging
  • DeepACSON automated segmentation of white matter in 3D electron microscopy (2021) in Communications Biology

Tohka's research is reflected in several main fields of study:

  • Medicine

Within this broad category, their work focuses on several subfields:

  • Radiology, Nuclear Medicine and Imaging
  • Neurology
  • Psychiatry and Mental health
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

The core topics addressed in their research include:

  • Advanced Neuroimaging Techniques and Applications
  • Dementia and Cognitive Impairment Research
  • Functional Brain Connectivity Studies
  • Brain Tumor Detection and Classification
  • Traumatic Brain Injury and Neurovascular Disturbances
  • Machine Learning in Healthcare
  • Advanced MRI Techniques and Applications

Tohka frequently collaborates with several researchers, indicating ongoing partnerships in their academic network. Their frequent co-authors are:

  • Alejandra Sierra
  • Ali Abdollahzadeh
  • Olli Gröhn
  • Vandad Imani
  • Riccardo De Feo

The publication venues where they have most frequently appeared include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Frontiers in Neuroscience
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Epilepsia

Tohka's academic profile demonstrates significant involvement in multidisciplinary research that leverages machine learning and advanced imaging methodologies to address neurological and psychiatric conditions. Their work spans both foundational reviews and applied imaging challenges, contributing to evolving techniques in biomedical imaging and health informatics.

Best Publications

  • Fast and robust parameter estimation for statistical partial volume models in brain MRI.

    Jussi Tohka;Alex P. Zijdenbos;Alan C. Evans

  • Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

    Elaheh Moradi;Antonietta Pepe;Christian Gaser;Heikki Huttunen

  • Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

    Esther E. Bron;Marion Smits;Wiesje M. van der Flier;Hugo Vrenken

  • Automatic independent component labeling for artifact removal in fMRI.

    Jussi Tohka;Karin Foerde;Karin Foerde;Adam R. Aron;Adam R. Aron;Sabrina M. Tom;Sabrina M. Tom

  • Inter-subject correlation of brain hemodynamic responses during watching a movie: localization in space and frequency.

    Jukka-Pekka Kauppi;Iiro P. Jääskeläinen;Mikko Sams;Jussi Tohka

  • Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand Challenge

    Sylvia Rueda;Sana Fathima;Caroline L. Knight;Mohammad Yaqub

  • Rey's Auditory Verbal Learning Test scores can be predicted from whole brain MRI in Alzheimer's disease.

    Elaheh Moradi;Ilona Hallikainen;Tuomo Hänninen;Jussi Tohka

  • Deconvolution-based partial volume correction in Raclopride-PET and Monte Carlo comparison to MR-based method.

    Jussi Tohka;Anthonin Reilhac

  • Genetic Algorithms for Finite Mixture Model Based Voxel Classification in Neuroimaging

    J. Tohka;E. Krestyannikov;I.D. Dinov;A.M. Graham

  • Evaluation of machine learning algorithms for health and wellness applications: A tutorial.

    Jussi Tohka;Mark J. van Gils

  • Inter-Subject Correlation in fMRI: Method Validation against Stimulus-Model Based Analysis

    Juha Pajula;Jukka Pekka Kauppi;Jussi Tohka

  • Transfer Learning in Magnetic Resonance Brain Imaging: a Systematic Review

    Juan Miguel Valverde;Vandad Imani;Ali Abdollahzadeh;Riccardo De Feo

  • Prediction of brain maturity based on cortical thickness at different spatial resolutions

    Budhachandra S. Khundrakpam;Jussi Tohka;Alan C. Evans

  • PET-SORTEO: validation and development of database of Simulated PET volumes

    A. Reilhac;G. Batan;C. Michel;C. Grova

  • Partial volume effect modeling for segmentation and tissue classification of brain magnetic resonance images: A review

    Jussi Tohka

  • How many is enough? effect of sample size in inter-subject correlation analysis of fMRI

    Juha Pajula;Jussi Tohka

  • T1 white/gray contrast as a predictor of chronological age, and an index of cognitive performance.

    John D Lewis;Alan C Evans;Jussi Tohka

  • Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia

    Jussi Tohka;Elaheh Moradi;Heikki Huttunen

  • Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data

    Elaheh Moradi;Budhachandra S. Khundrakpam;John D. Lewis;Alan C. Evans

  • Brain MRI tissue classification based on local Markov random fields

    Jussi Tohka;Ivo D. Dinov;David W. Shattuck;Arthur W. Toga

  • A versatile software package for inter-subject correlation based analyses of fMRI.

    Jukka Pekka Kauppi;Jukka Pekka Kauppi;Juha Pajula;Jussi Tohka

Frequent Co-Authors

Alan C. Evans
Alan C. Evans McGill University
Olli Gröhn
Olli Gröhn University of Eastern Finland
Rashid Giniatullin
Rashid Giniatullin University of Eastern Finland
Vesa Kiviniemi
Vesa Kiviniemi Oulu University Hospital
Eija Jokitalo
Eija Jokitalo University of Helsinki
Pierrick Coupé
Pierrick Coupé University of Bordeaux
José V. Manjón
José V. Manjón Universitat Politècnica de València
Asla Pitkänen
Asla Pitkänen University of Eastern Finland
Iiro P. Jääskeläinen
Iiro P. Jääskeläinen Aalto University
Jouko Miettunen
Jouko Miettunen Oulu University Hospital

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