Articles with public access mandates - Patrick LeoLearn more
Not available anywhere: 6
Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images
P Leo, G Lee, A Madabhushi
SPIE Medical Imaging, 97910I-97910I-13, 2016
Mandates: US National Institutes of Health
Compactness measures of tumor infiltrating lymphocytes in lung adenocarcinoma are associated with overall patient survival and immune scores
R Ding, P Prasanna, G Corredor, C Lu, P Velu, K Le, P Leo, N Beig, ...
Medical Imaging 2020: Digital Pathology 11320, 1132003, 2020
Mandates: US Department of Defense, US National Institutes of Health, US Department of …
Three-dimensional histo-morphometric features from light sheet microscopy images result in improved discrimination of benign from malignant glands in prostate cancer
CF Koyuncu, A Janowczyk, C Lu, P Leo, M Alilou, AK Glaser, NP Reder, ...
Medical Imaging 2020: Digital Pathology 11320, 109-116, 2020
Mandates: US National Science Foundation, US Department of Defense, US National …
SPARTA: An integrated stability, discriminability, and sparsity based radiomic feature selection approach
AR Sadri, S Azarianpour Esfahani, P Chirra, J Antunes, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
Mandates: US Department of Defense, US National Institutes of Health
Texture features distinguish benign cell clusters from adenocarcinomas on bile duct brushing cytology images
S Monabbati, P Leo, K Bera, BG Nezami, CW Michael, A Harbhajanka, ...
Medical Imaging 2020: Digital Pathology 11320, 123-133, 2020
Mandates: US Department of Defense, US National Institutes of Health, US Department of …
COMPUTER-EXTRACTED FEATURES OF NUCLEAR AND GLANDULAR MORPHOLOGY FROM DIGITAL H&E TISSUE IMAGES PREDICT PROSTATE CANCER BIOCHEMICAL RECURRENCE AND METASTASIS FOLLOWING RADICAL …
P Leo, A Gawlik, G Zhu, M Feldman, S Gupta, R Veltri, A Madabhushi
Journal of Urology 199 (4), e446-e447, 2018
Mandates: US Department of Defense, US National Institutes of Health
Available somewhere: 27
Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images
P Leo, G Lee, NNC Shih, R Elliott, MD Feldman, A Madabhushi
Journal of medical imaging 3 (4), 047502-047502, 2016
Mandates: US National Institutes of Health
Prostate cancer risk stratification via nondestructive 3D pathology with deep learning–assisted gland analysis
W Xie, NP Reder, C Koyuncu, P Leo, S Hawley, H Huang, C Mao, ...
Cancer research 82 (2), 334-345, 2022
Mandates: US National Science Foundation, US Department of Defense, US National …
Computationally derived image signature of stromal morphology is prognostic of prostate cancer recurrence following prostatectomy in African American patients
HK Bhargava, P Leo, R Elliott, A Janowczyk, J Whitney, S Gupta, P Fu, ...
Clinical Cancer Research 26 (8), 1915-1923, 2020
Mandates: US National Science Foundation, US Department of Defense, US National …
Feature-driven local cell graph (FLocK): new computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers
C Lu, C Koyuncu, G Corredor, P Prasanna, P Leo, XX Wang, ...
Medical image analysis 68, 101903, 2021
Mandates: US National Science Foundation, US Department of Defense, US National …
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, 2021
Mandates: Swiss National Science Foundation, US Department of Defense, US National …
Multisite evaluation of radiomic feature reproducibility and discriminability for identifying peripheral zone prostate tumors on MRI
P Chirra, P Leo, M Yim, BN Bloch, AR Rastinehad, A Purysko, M Rosen, ...
Journal of Medical Imaging 6 (2), 024502-024502, 2019
Mandates: US Department of Defense, US National Institutes of Health, US Department of …
Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study
P Leo, R Elliott, NNC Shih, S Gupta, M Feldman, A Madabhushi
Scientific reports 8 (1), 14918, 2018
Mandates: US National Science Foundation, US Department of Defense, US National …
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
Mandates: US Department of Defense, US National Institutes of Health, US Department of …
T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning–derived estimates of epithelium, lumen, and stromal composition on …
R Shiradkar, A Panda, P Leo, A Janowczyk, X Farre, N Janaki, L Li, ...
European radiology 31, 1336-1346, 2021
Mandates: US Department of Defense, US National Institutes of Health, US Department of …
Empirical evaluation of cross-site reproducibility in radiomic features for characterizing prostate MRI
P Chirra, P Leo, M Yim, BN Bloch, AR Rastinehad, A Purysko, M Rosen, ...
Medical imaging 2018: computer-aided diagnosis 10575, 67-78, 2018
Mandates: US Department of Defense, US National Institutes of Health
Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome
R Ding, P Prasanna, G Corredor, C Barrera, P Zens, C Lu, P Velu, P Leo, ...
NPJ precision oncology 6 (1), 33, 2022
Mandates: US National Science Foundation, US Department of Defense, US National …
Computationally derived cribriform area index from prostate cancer hematoxylin and eosin images is associated with biochemical recurrence following radical prostatectomy and is …
P Leo, S Chandramouli, X Farre, R Elliott, A Janowczyk, K Bera, P Fu, ...
European urology focus 7 (4), 722-732, 2021
Mandates: US National Science Foundation, US Department of Defense, US National …
Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study
P Leo, A Janowczyk, R Elliott, N Janaki, K Bera, R Shiradkar, X Farré, ...
NPJ precision oncology 5 (1), 35, 2021
Mandates: US National Science Foundation, US Department of Defense, US National …
Computer extracted features from initial H&E tissue biopsies predict disease progression for prostate cancer patients on active surveillance
S Chandramouli, P Leo, G Lee, R Elliott, C Davis, G Zhu, P Fu, JI Epstein, ...
Cancers 12 (9), 2708, 2020
Mandates: US National Science Foundation, US Department of Defense, US National …
Publication and funding information is determined automatically by a computer program