Ashirbani Saha
Ashirbani Saha
Assistant Professor, Department of Oncology, McMaster University
E-mailová adresa ověřena na: - Domovská stránka
Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI
MA Mazurowski, M Buda, A Saha, MR Bashir
Journal of magnetic resonance imaging 49 (4), 939-954, 2019
Deep learning for segmentation of brain tumors: Impact of cross‐institutional training and testing
EA AlBadawy, A Saha, MA Mazurowski
Medical physics 45 (3), 1150-1158, 2018
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
M Buda, A Saha, MA Mazurowski
Computers in biology and medicine 109, 218-225, 2019
Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set
EH Cain, A Saha, MR Harowicz, JR Marks, PK Marcom, MA Mazurowski
Breast cancer research and treatment 173, 455-463, 2019
Deep learning for identifying radiogenomic associations in breast cancer
Z Zhu, E Albadawy, A Saha, J Zhang, MR Harowicz, MA Mazurowski
Computers in biology and medicine 109, 85-90, 2019
Hierarchical convolutional neural networks for segmentation of breast tumors in MRI with application to radiogenomics
J Zhang, A Saha, Z Zhu, MA Mazurowski
IEEE transactions on medical imaging 38 (2), 435-447, 2018
A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features
A Saha, MR Harowicz, LJ Grimm, CE Kim, SV Ghate, R Walsh, ...
British journal of cancer 119 (4), 508-516, 2018
Radiogenomics of lower-grade glioma: algorithmically-assessed tumor shape is associated with tumor genomic subtypes and patient outcomes in a multi-institutional study with The …
MA Mazurowski, K Clark, NM Czarnek, P Shamsesfandabadi, KB Peters, ...
Journal of neuro-oncology 133, 27-35, 2017
Effects of MRI scanner parameters on breast cancer radiomics
A Saha, X Yu, D Sahoo, MA Mazurowski
Expert systems with applications 87, 384-391, 2017
Utilizing image scales towards totally training free blind image quality assessment
A Saha, QMJ Wu
IEEE Transactions on Image Processing 24 (6), 1879-1892, 2015
Mutual spectral residual approach for multifocus image fusion
A Saha, G Bhatnagar, QMJ Wu
Digital Signal Processing 23 (4), 1121-1135, 2013
Breast cancer MRI radiomics: An overview of algorithmic features and impact of inter‐reader variability in annotating tumors
A Saha, MR Harowicz, MA Mazurowski
Medical physics 45 (7), 3076-3085, 2018
Full-reference image quality assessment by combining global and local distortion measures
A Saha, QMJ Wu, 2014
A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models
A Saha, MR Harowicz, W Wang, MA Mazurowski
Journal of cancer research and clinical oncology 144, 799-807, 2018
Relationship between background parenchymal enhancement on high-risk screening MRI and future breast cancer risk
LJ Grimm, A Saha, SV Ghate, C Kim, MS Soo, SC Yoon, MA Mazurowski
Academic radiology 26 (1), 69-75, 2019
Facial expression recognition using curvelet based local binary patterns
A Saha, QMJ Wu
2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010
Algorithms for prediction of the Oncotype DX recurrence score using clinicopathologic data: a review and comparison using an independent dataset
MR Harowicz, TJ Robinson, MA Dinan, A Saha, JR Marks, PK Marcom, ...
Breast cancer research and treatment 162, 1-10, 2017
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ
Z Zhu, M Harowicz, J Zhang, A Saha, LJ Grimm, ES Hwang, ...
Computers in biology and medicine 115, 103498, 2019
Ethical concerns around use of artificial intelligence in health care research from the perspective of patients with meningioma, caregivers and health care providers: a …
MD McCradden, A Baba, A Saha, S Ahmad, K Boparai, P Fadaiefard, ...
Canadian Medical Association Open Access Journal 8 (1), E90-E95, 2020
Can algorithmically assessed MRI features predict which patients with a preoperative diagnosis of ductal carcinoma in situ are upstaged to invasive breast cancer?
MR Harowicz, A Saha, LJ Grimm, PK Marcom, JR Marks, ES Hwang, ...
Journal of magnetic resonance imaging 46 (5), 1332-1340, 2017
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Články 1–20