E
Ebrahim Nasr-Esfahani
Researcher at Isfahan University of Technology
Publications - 23
Citations - 988
Ebrahim Nasr-Esfahani is an academic researcher from Isfahan University of Technology. The author has contributed to research in topics: Segmentation & Image compression. The author has an hindex of 13, co-authored 22 publications receiving 668 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
Polyp Segmentation in Colonoscopy Images Using Fully Convolutional Network
Mojtaba Akbari,Majid Mohrekesh,Ebrahim Nasr-Esfahani,S. M. Reza Soroushmehr,Nader Karimi,Shadrokh Samavi,Kayvan Najarian +6 more
TL;DR: Wang et al. as discussed by the authors proposed a polyp segmentation method based on the convolutional neural network, which performed a novel image patch selection method in the training phase of the network and performed effective post-processing on the probability map that is produced by the network.
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
Extraction of skin lesions from non-dermoscopic images for surgical excision of melanoma.
M. Hossein Jafari,Ebrahim Nasr-Esfahani,Nader Karimi,S. M. Reza Soroushmehr,Shadrokh Samavi,Shadrokh Samavi,Kayvan Najarian +6 more
TL;DR: A new method based on deep neural networks is proposed for accurate extraction of a lesion region and can outperform other state-of-the-art algorithms exist in the literature.
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.