S
S.M.R. Soroushmehr
Researcher at University of Michigan
Publications - 29
Citations - 902
S.M.R. Soroushmehr is an academic researcher from University of Michigan. The author has contributed to research in topics: Segmentation & Convolutional neural network. The author has an hindex of 13, co-authored 29 publications receiving 660 citations.
Papers
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Proceedings ArticleDOI
Melanoma detection by analysis of clinical images using convolutional neural network
Ebrahim Nasr-Esfahani,Shadrokh Samavi,Nader Karimi,S.M.R. Soroushmehr,Mohammad H. Jafari,Kevin R. Ward,Kayvan Najarian +6 more
TL;DR: Experimental results show that the proposed method for detection of melanoma lesions is superior in terms of diagnostic accuracy in comparison with the state-of-the-art methods.
Proceedings ArticleDOI
Skin lesion segmentation in clinical images using deep learning
Mohammad H. Jafari,Nader Karimi,Ebrahim Nasr-Esfahani,Shadrokh Samavi,S.M.R. Soroushmehr,Kevin R. Ward,Kayvan Najarian +6 more
TL;DR: The experimental results show that the proposed method for accurate extraction of lesion region can outperform the existing state-of-the-art algorithms in terms of segmentation accuracy.
Journal ArticleDOI
Deep learning in pharmacogenomics: from gene regulation to patient stratification.
Alexandr A. Kalinin,Gerald A. Higgins,Narathip Reamaroon,S.M.R. Soroushmehr,Ari Allyn-Feuer,Ivo D. Dinov,Kayvan Najarian,Brian D. Athey +7 more
TL;DR: This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: identification of novel regulatory variants located in noncoding domains of the genome and their function as applied to pharmacoepigenomics; patient stratification from medical records; and the mechanistic prediction of drug response, targets and their interactions.
Proceedings ArticleDOI
Vessel extraction in X-ray angiograms using deep learning
Ebrahim Nasr-Esfahani,Shadrokh Samavi,Nader Karimi,S.M.R. Soroushmehr,Kevin R. Ward,Mohammad H. Jafari,B. Felfeliyan,Brahmajee K. Nallamothu,Kayvan Najarian +8 more
TL;DR: Experimental results on angiography images of a dataset show that the proposed deep learning approach using convolutional neural networks has a superior performance in extraction of vessel regions.
Journal ArticleDOI
Segmentation of vessels in angiograms using convolutional neural networks
Ebrahim Nasr-Esfahani,Nader Karimi,Mohammad H. Jafari,S.M.R. Soroushmehr,Shadrokh Samavi,Shadrokh Samavi,Brahmajee K. Nallamothu,Kayvan Najarian +7 more
TL;DR: A method for detecting vessel regions in angiography images is proposed which is based on deep learning approach using convolutional neural networks (CNN) and results show its superiority in extraction of vessels regions in comparison to state of the art methods.