|Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme|
EI Zacharaki, S Wang, S Chawla, D Soo Yoo, R Wolf, ER Melhem, ...
Magnetic Resonance in Medicine: An Official Journal of the International …, 2009
|Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology|
EJ Limkin, R Sun, L Dercle, EI Zacharaki, C Robert, S Reuzé, ...
Annals of Oncology 28 (6), 1191-1206, 2017
|Multiparametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images|
R Verma, EI Zacharaki, Y Ou, H Cai, S Chawla, SK Lee, ER Melhem, ...
Academic radiology 15 (8), 966-977, 2008
|ORBIT: A multiresolution framework for deformable registration of brain tumor images|
EI Zacharaki, D Shen, SK Lee, C Davatzikos
IEEE transactions on medical imaging 27 (8), 1003-1017, 2008
|Deformable registration of brain tumor images via a statistical model of tumor-induced deformation|
A Mohamed, EI Zacharaki, D Shen, C Davatzikos
Medical image analysis 10 (5), 752-763, 2006
|In silico radiation oncology: combining novel simulation algorithms with current visualization techniques|
GS Stamatakos, DD Dionysiou, EI Zacharaki, NA Mouravliansky, ...
Proceedings of the IEEE 90 (11), 1764-1777, 2002
|Non-diffeomorphic registration of brain tumor images by simulating tissue loss and tumor growth|
EI Zacharaki, CS Hogea, D Shen, G Biros, C Davatzikos
Neuroimage 46 (3), 762-774, 2009
|Measuring brain lesion progression with a supervised tissue classification system|
EI Zacharaki, S Kanterakis, RN Bryan, C Davatzikos
International Conference on Medical Image Computing and Computer-assisted …, 2008
|STEP: Spatiotemporal enhancement pattern for MR‐based breast tumor diagnosis|
Y Zheng, S Englander, S Baloch, EI Zacharaki, Y Fan, MD Schnall, ...
Medical physics 36 (7), 3192-3204, 2009
|Survival analysis of patients with high-grade gliomas based on data mining of imaging variables|
EI Zacharaki, N Morita, P Bhatt, DM O'rourke, ER Melhem, C Davatzikos
American Journal of Neuroradiology 33 (6), 1065-1071, 2012
|Investigating machine learning techniques for MRI-based classification of brain neoplasms|
EI Zacharaki, VG Kanas, C Davatzikos
International journal of computer assisted radiology and surgery 6 (6), 821-828, 2011
|A digital subtraction radiography scheme based on automatic multiresolution registration|
EI Zacharaki, GK Matsopoulos, PA Asvestas, KS Nikita, K Grondahl, ...
Dentomaxillofacial radiology 33 (6), 379-390, 2004
|MRI-based classification of brain tumor type and grade using SVM-RFE|
EI Zacharaki, S Wang, S Chawla, DS Yoo, R Wolf, ER Melhem, ...
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro …, 2009
|Seizure detection using EEG and ECG signals for computer-based monitoring, analysis and management of epileptic patients|
I Mporas, V Tsirka, EI Zacharaki, M Koutroumanidis, M Richardson, ...
Expert systems with applications 42 (6), 3227-3233, 2015
|Simulating growth dynamics and radiation response of avascular tumour spheroids—model validation in the case of an EMT6/Ro multicellular spheroid|
EI Zacharaki, GS Stamatakos, KS Nikita, NK Uzunoglu
Computer methods and programs in biomedicine 76 (3), 193-206, 2004
|Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma|
VG Kanas, EI Zacharaki, GA Thomas, PO Zinn, V Megalooikonomou, ...
Computer methods and programs in biomedicine 140, 249-257, 2017
|A comparative study of biomechanical simulators in deformable registration of brain tumor images|
EI Zacharaki, CS Hogea, G Biros, C Davatzikos
IEEE Transactions on Biomedical Engineering 55 (3), 1233-1236, 2008
|Improving classification of epileptic and non-epileptic EEG events by feature selection|
E Pippa, EI Zacharaki, I Mporas, V Tsirka, MP Richardson, ...
Neurocomputing 171, 576-585, 2016
|A low cost approach for brain tumor segmentation based on intensity modeling and 3D Random Walker|
VG Kanas, EI Zacharaki, C Davatzikos, KN Sgarbas, V Megalooikonomou
Biomedical Signal Processing and Control 22, 19-30, 2015
|EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation|
A Amidi, S Amidi, D Vlachakis, V Megalooikonomou, N Paragios, ...
PeerJ 6, e4750, 2018