Research Topics
| Jussi TohkaSummaryAffiliation: Tampere University of Technology Country: Finland Publications
| Collaborators
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Detail Information
Publications
Shape analysis of human brain interhemispheric fissure bending in MRILu Zhao
Department of Signal Processing, Tampere University of Technology, FIN 33101, Tampere, Finland
Med Image Comput Comput Assist Interv 12:216-23. 2009..These results show that our method is applicable for studying abnormal Yakovlevian torque related to mental diseases...
The impact of sampling density upon cortical network analysis: regions or pointsJussi Tohka
Department of Signal Processing, Tampere University of Technology, P O Box 553, FIN 33101, Finland
Magn Reson Imaging 30:978-92. 2012..Finally, a similar methodology as the one used here could be used to study effects of the sampling density in other brain-imaging-based networks, for example, in resting-state functional MRI...- Deconvolution-based partial volume correction in Raclopride-PET and Monte Carlo comparison to MR-based methodJussi Tohka
Institute of Signal Processing, Tampere University of Technology, Tampere, Finland
Neuroimage 39:1570-84. 2008..Moreover, PV-corrected parametric images can be readily computed based on deconvolved dynamic images... 
Brain MRI tissue classification based on local Markov random fieldsJussi Tohka
Department of Signal Processing, Tampere University of Technology, P O Box 553, FIN 33101, Finland
Magn Reson Imaging 28:557-73. 2010..The method also offers better protection against intensity non-uniformity artifact than the corresponding method based on a global (whole image) modeling scheme...- Automatic independent component labeling for artifact removal in fMRIJussi Tohka
Institute of Signal Processing, Tampere University of Technology, Tampere, Finland
Neuroimage 39:1227-45. 2008..We conclude that automatic ICA-based denoising offers a potentially useful approach to improve the quality of fMRI data and consequently increase the accuracy of the statistical analysis of these data... - Genetic algorithms for finite mixture model based voxel classification in neuroimagingJussi Tohka
Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, University of California, Los Angeles, CA 90095, USA
IEEE Trans Med Imaging 26:696-711. 2007..The tissue classification results by our method are shown to be consistently more reliable and accurate than with the competing parameter estimation methods... - Fast and robust parameter estimation for statistical partial volume models in brain MRIJussi Tohka
Digital Media Institute Signal Processing, Tampere University of Technology, FIN 33101, Finland
Neuroimage 23:84-97. 2004.... - Automatic cerebral and cerebellar hemisphere segmentation in 3D MRI: adaptive disconnection algorithmLu Zhao
Department of Signal Processing, Tampere University of Technology, P O Box 553, FIN 33101 Tampere, Finland
Med Image Anal 14:360-72. 2010..A preliminary cerebral volumetric asymmetry analysis based on these images demonstrated that the Adaptive Disconnection method is applicable to study abnormal brain asymmetry in schizophrenia... - Unsupervised segmentation of cardiac PET transmission images for automatic heart volume extractionAnu Juslin
Institute of Signal Processing, Tampere University of Technology, Tampere, Finland
Conf Proc IEEE Eng Med Biol Soc 1:1077-80. 2006..The method was tested with 25 patient images. The MRF segmentation results were of good quality in all cases and we were able to extract the heart volume from all the images... - Evaluation of the automatic three-dimensional delineation of caudate and putamen for PET receptor occupancy studiesEsa Wallius
Institute of Signal Processing, Tampere University of Technology, Tampere, Finland
Nucl Med Commun 29:53-65. 2008..The aim of this study was to evaluate, and confirm the feasibility of two automatic, paired, three-dimensional delineation methods of striatal structures (caudate and putamen) for the purposes of PET receptor occupancy studies... - Automatic compartmental decomposition for 3D MR images of human brainLu Zhao
Department of Signal Processing, Tampere University of Technology, Finland
Conf Proc IEEE Eng Med Biol Soc 2008:3888-91. 2008..It was demonstrated to be accurate and robust, and the mean Dice coefficients for cerebrum, cerebellum and brainstem were 0.99, 0.98 and 0.82, respectively... - Automatic statistical shape analysis of cerebral asymmetry in 3D T1-weighted magnetic resonance images at vertex-level: Application to neuroleptic-naïve schizophreniaAntonietta Pepe
Department of Signal Processing, Tampere University of Technology, P O Box 553, FIN 33101 Tampere, Finland Electronic address
Magn Reson Imaging 31:676-87. 2013..The findings of this study, although need further testing in larger samples, partially replicate previous studies supporting the hypothesis of schizophrenia as a neurodevelopmental disorder... - Inter-subject correlation in fMRI: method validation against stimulus-model based analysisJuha Pajula
Department of Signal Processing, Tampere University of Technology, Tampere, Finland
PLoS ONE 7:e41196. 2012..The agreement of the results is highly interesting, because ISC is applicable in situations where GLM is not suitable, for example, when analyzing data from a naturalistic stimuli experiment... - Robust MRI brain tissue parameter estimation by multistage outlier rejectionJosé V Manjón
IBIME Group, ITACA Institute, Polytechnic University of Valencia, Valencia, Spain
Magn Reson Med 59:866-73. 2008..The proposed method has been evaluated using both synthetic and real MR data and compared with state-of-the-art methods showing the best results in the comparative... - Automatic extraction of brain surface and mid-sagittal plane from PET images applying deformable modelsJouni Mykkänen
Department of Computer Sciences, University of Tampere, Kanslerinrinne 1, Pinni B1039, FIN 33014, Finland
Comput Methods Programs Biomed 79:1-17. 2005..The proposed segmentation methods provide a promising direction for automatic processing and analysis of PET brain images... - Robust estimation of bioaffinity assay fluorescence signalsDimitris Glotsos
Medical Image Processing and Analysis Unit, Medical Physics Laboratory, University of Patras, Patras, Greece
IEEE Trans Inf Technol Biomed 10:733-9. 2006.... - Automated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machinesDimitris Glotsos
Department of Medical Physics, University of Patras, Rio Patras 26500, Greece
Int J Neural Syst 15:1-11. 2005..5%. Low, intermediate, and high-grade tumours were identified with 95%, 88.3%, and 91% accuracies respectively. The proposed algorithm could be used as a second opinion tool for the histopathologists... - Delineation of brain structures from positron emission tomography images with deformable modelsJouni Mykkänen
Department of Computer and Information Sciences, University of Tampere, Finland
Stud Health Technol Inform 95:33-8. 2003..The proposed method provides new opportunities for automatic and repeatable structure extraction applicable for regional quantification of the tracer uptake...