Mehdi Alilou
Mehdi Alilou
Research Assistant Professor, Case Western Reserve University
Geverifieerd e-mailadres voor case.edu
Geciteerd door
Geciteerd door
Perinodular and intranodular radiomic features on lung CT images distinguish adenocarcinomas from granulomas
N Beig, M Khorrami, M Alilou, P Prasanna, N Braman, M Orooji, S Rakshit, ...
Radiology 290 (3), 783-792, 2019
Changes in CT radiomic features associated with lymphocyte distribution predict overall survival and response to immunotherapy in non–small cell lung cancer
M Khorrami, P Prasanna, A Gupta, P Patil, PD Velu, R Thawani, ...
Cancer immunology research 8 (1), 108-119, 2020
Novel, non-invasive imaging approach to identify patients with advanced non-small cell lung cancer at risk of hyperprogressive disease with immune checkpoint blockade
P Vaidya, K Bera, PD Patil, A Gupta, P Jain, M Alilou, M Khorrami, ...
Journal for Immunotherapy of Cancer 8 (2), 2020
A comprehensive framework for automatic detection of pulmonary nodules in lung CT images
M Alilou, V Kovalev, E Snezhko, V Taimouri
Image Analysis and Stereology 33 (1), 13-27, 2014
Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features
M Khorrami, P Jain, K Bera, M Alilou, R Thawani, P Patil, U Ahmad, ...
Lung Cancer 135, 1-9, 2019
An integrated segmentation and shape‐based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT
M Alilou, N Beig, M Orooji, P Rajiah, V Velcheti, S Rakshit, N Reddy, ...
Medical physics 44 (7), 3556-3569, 2017
Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study
M Khorrami, K Bera, P Leo, P Vaidya, P Patil, R Thawani, P Velu, P Rajiah, ...
Lung Cancer 142, 90-97, 2020
Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas
M Alilou, M Orooji, N Beig, P Prasanna, P Rajiah, C Donatelli, V Velcheti, ...
Scientific reports 8 (1), 15290, 2018
Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography
M Orooji, M Alilou, S Rakshit, N Beig, MH Khorrami, P Rajiah, R Thawani, ...
Journal of Medical Imaging 5 (2), 024501-024501, 2018
Upgrading performance of DSR routing protocol in mobile ad hoc networks
M Alilou, M Dehghan
International Journal of Electronics and Communication Engineering 1 (5 …, 2007
Automatic object detection and segmentation of the histocytology images using reshapable agents
M Alilou, V Kovalev
Image Analysis and Stereology 32 (2), 89-99, 2013
Radiomics-based assessment of ultra-widefield leakage patterns and vessel network architecture in the PERMEATE study: insights into treatment durability
P Prasanna, V Bobba, N Figueiredo, DD Sevgi, C Lu, N Braman, M Alilou, ...
British Journal of Ophthalmology 105 (8), 1155-1160, 2021
Segmentation of cell nuclei in heterogeneous microscopy images: A reshapable templates approach
M Alilou, V Kovalev, V Taimouri
Computerized Medical Imaging and Graphics 37 (7-8), 488-499, 2013
Integrated clinical and CT based artificial intelligence nomogram for predicting severity and need for ventilator support in COVID-19 patients: a multi-site study
A Hiremath, K Bera, L Yuan, P Vaidya, M Alilou, J Furin, K Armitage, ...
IEEE journal of biomedical and health informatics 25 (11), 4110-4118, 2021
Vascular network organization via hough transform (VaNgOGH): a novel radiomic biomarker for diagnosis and treatment response
N Braman, P Prasanna, M Alilou, N Beig, A Madabhushi
International Conference on Medical Image Computing and Computer-Assisted …, 2018
Intra-perinodular textural transition (IPRIS): a three dimenisonal (3D) descriptor for nodule diagnosis on lung computed tomography (CT) images
A Madabhushi, M Alilou
US Patent 10,692,211, 2020
A combination of intra-and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint …
M Khorrami, M Alilou, P Prasanna, P Patil, P Velu, K Bera, P Fu, ...
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 191-199, 2019
Predicting immunotherapy response in non-small cell lung cancer patients with quantitative vessel tortuosity
A Madabhushi, M Alilou, V Velcheti
US Patent 10,492,723, 2019
Quantitative vessel tortuosity radiomics on baseline non-contrast lung CT predict response to immunotherapy and are prognostic of overall survival
M Alilou, P Vaidya, M Khorrami, A Zagouras, P Patil, K Bera, P Fu, ...
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 365-372, 2019
Characterizing disease and treatment response with quantitative vessel tortuosity radiomics
A Madabhushi, M Orooji, M Rusu, P Linden, R Gilkeson, NM Braman, ...
US Patent 10,064,594, 2018
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