|ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional networks|
AG Roy, S Conjeti, SPK Karri, D Sheet, A Katouzian, C Wachinger, ...
Biomedical optics express 8 (8), 3627-3642, 2017
|Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography|
HA Kirişli, M Schaap, CT Metz, AS Dharampal, WB Meijboom, ...
Medical image analysis 17 (8), 859-876, 2013
|A State of The Art Review on Segmentation Algorithms in Intravascular Ultrasound (IVUS) Images|
A Katouzian, E Angelini, S Carlier, J Suri, N Navab, A Laine
|Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open …|
J Guinney, T Wang, TD Laajala, KK Winner, JC Bare, EC Neto, SA Khan, ...
The Lancet Oncology 18 (1), 132-142, 2017
|Challenges in atherosclerotic plaque characterization with intravascular ultrasound (IVUS): From data collection to classification|
A Katouzian, S Sathyanarayana, B Baseri, EE Konofagou, S Carlier
Information Technology in Biomedicine, IEEE Transactions on 12 (3), 315-327, 2008
|Segmentation By Retrieval With Guided Random Walks: Application To Left Ventricle Segmentation in MRI|
A Eslami, A Karamalis, A Katouzian, N Navab
Medical image analysis, 2012
|Error corrective boosting for learning fully convolutional networks with limited data|
AG Roy, S Conjeti, D Sheet, A Katouzian, N Navab, C Wachinger
International Conference on Medical Image Computing and Computer-Assisted …, 2017
|A new automated technique for left-and right-ventricular segmentation in magnetic resonance imaging|
A Katouzian, A Prakash, E Konofagou
2006 International Conference of the IEEE Engineering in Medicine and …, 2006
|Automatic detection of blood versus non-blood regions on intravascular ultrasound (IVUS) images using wavelet packet signatures|
A Katouzian, B Baseri, EE Konofagou, AF Laine
Medical imaging 2008: Ultrasonic imaging and signal processing: 17-18 …, 2008
|Fast training of support vector machines for survival analysis|
S Pölsterl, N Navab, A Katouzian
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
|Lumen segmentation in intravascular optical coherence tomography using backscattering tracked and initialized random walks|
AG Roy, S Conjeti, SG Carlier, PK Dutta, A Kastrati, AF Laine, N Navab, ...
IEEE journal of biomedical and health informatics 20 (2), 606-614, 2015
|Iterative Self-Organizing Atherosclerotic Tissue Labeling in Intravascular Ultrasound Images and Comparison with Virtual Histology|
A Katouzian, A Karamalis, E Konofagou, B Baseri, S Carlier, A Koenig, ...
|3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation|
M Riva, C Hennersperger, F Milletari, A Katouzian, F Pessina, ...
International journal of computer assisted radiology and surgery 12 (10 …, 2017
|Survival analysis for high-dimensional, heterogeneous medical data: Exploring feature extraction as an alternative to feature selection|
S Pölsterl, S Conjeti, N Navab, A Katouzian
Artificial intelligence in medicine 72, 1-11, 2016
|Deeply learnt hashing forests for content based image retrieval in prostate MR images|
A Shah, S Conjeti, N Navab, A Katouzian
Medical Imaging 2016: Image Processing 9784, 978414, 2016
|Parsing human skeletons in an operating room|
V Belagiannis, X Wang, HBB Shitrit, K Hashimoto, R Stauder, Y Aoki, ...
Machine Vision and Applications 27 (7), 1035-1046, 2016
|Characterization of the intravascular ultrasound radiofrequency signal within regions of acoustic shadowing behind calcium|
K Tanak, SG Cartier, A Katouzian, GS Mintz
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY 49 (9), 29B-29B, 2007
|An efficient training algorithm for kernel survival support vector machines|
S Pölsterl, N Navab, A Katouzian
arXiv preprint arXiv:1611.07054, 2016
|Supervised domain adaptation of decision forests: Transfer of models trained in vitro for in vivo intravascular ultrasound tissue characterization|
S Conjeti, A Katouzian, AG Roy, L Peter, D Sheet, S Carlier, A Laine, ...
Medical image analysis 32, 1-17, 2016
|Heterogeneous ensembles for predicting survival of metastatic, castrate-resistant prostate cancer patients|
S Pölsterl, P Gupta, L Wang, S Conjeti, A Katouzian, N Navab
F1000Research 5, 2016