Ahmad Algohary
Ahmad Algohary
Verified email at case.edu
Title
Cited by
Cited by
Year
Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: preliminary findings from a multi‐institutional study
SB Ginsburg, A Algohary, S Pahwa, V Gulani, L Ponsky, HJ Aronen, ...
Journal of Magnetic Resonance Imaging 46 (1), 184-193, 2017
792017
Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI
R Shiradkar, TK Podder, A Algohary, S Viswanath, RJ Ellis, ...
Radiation oncology 11 (1), 1-14, 2016
592016
Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: preliminary findings
A Algohary, S Viswanath, R Shiradkar, S Ghose, S Pahwa, D Moses, ...
Journal of Magnetic Resonance Imaging 48 (3), 818-828, 2018
572018
Detection of cardiac infarction in MRI C-SENC images
AO Algohary, AM El-Bialy, AH Kandil, NF Osman
Universal journal of Computer science engineering technology 1, 36-40, 2010
92010
Improved segmentation technique to detect cardiac infarction in MRI C-SENC images
AO Algohary, AM El-Bialy, AH Kandil, NF Osman
2010 5th Cairo International Biomedical Engineering Conference, 21-24, 2010
62010
Quantitative assessment of T2-weighted MRI to better identify patients with prostate cancer in a screening population. 2015 American Urological Association (AUA) Meeting, May …
A Algohary, S Viswanath, P Prasanna, S Pahwa, V Gulani, D Moses, ...
New Orleans, LA, 2015
4*2015
Combination of peri-tumoral and intra-tumoral radiomic features on bi-parametric MRI accurately stratifies prostate cancer risk: A multi-site study
A Algohary, R Shiradkar, S Pahwa, A Purysko, S Verma, D Moses, ...
Cancers 12 (8), 2200, 2020
32020
Predicting prostate cancer risk of progression with multiparametric magnetic resonance imaging using machine learning and peritumoral radiomics
A Madabhushi, A Algohary, R Shiradkar
US Patent App. 16/395,904, 2020
22020
Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score
L Li, R Shiradkar, A Algohary, P Leo, C Magi-Galluzzi, E Klein, A Purysko, ...
Medical Imaging 2019: Computer-Aided Diagnosis 10950, 109503Y, 2019
22019
Association of radiomic features from prostate bi-parametric MRI with Decipher risk categories to predict risk for biochemical recurrence post-prostatectomy.
L Li, R Shiradkar, P Leo, A Purysko, A Algohary, EA Klein, ...
Journal of Clinical Oncology 37 (15_suppl), e16561-e16561, 2019
12019
A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI
L Li, R Shiradkar, P Leo, A Algohary, P Fu, SH Tirumani, A Mahran, ...
EBioMedicine 63, 103163, 2021
2021
PROSTATE CANCER RISK STRATIFICATION USING RADIOMICS FOR PATIENTS ON ACTIVE SURVEILLANCE: MULTI-INSTITUTIONAL USE CASES
A Algohary
Case Western Reserve University, 2020
2020
MP35-01 PROSTATE TUMOR TEXTURAL HETEROGENEITY OF 11C-ACETATE POSITRON EMISSION TOMOGRAPHY AND T2-WEIGHTED MAGNETIC …
L Li, I Jambor, P Taimen, H Merisaar, H Minn, P Bostrom, H Aronen, ...
The Journal of Urology 199 (4S), e446-e446, 2018
2018
A novel segmentation method to identify left ventricular infarction in short-axis composite strain-encoded magnetic resonance images
AO Algohary, MK Metwally, AM El-Bialy, AH Kandil, NF Osman
Medical Imaging 2011: Image Processing 7962, 79622E, 2011
2011
Improved segmentation technique to detect cardiac infarction in composite strain-encoded (C-sence) images
AO Algohary
Cairo University, 2010
2010
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Articles 1–15