202 citations · 295 across the 10 of their papers we have counts for
6 papers · 1 filter
Left ventricle segmentation By modelling uncertainty in prediction of deep convolutional neural networks and adaptive thresholding inference
Alireza Norouzi, Ali Emami, S. M. Reza Soroushmehr +3
Deep neural networks have shown great achievements in solving complex problems. However, there are fundamental problems that limit their real world applications. Lack of measurable…
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization
Mohsen Hajabdollahi, Reza Esfandiarpoor, S. M. Reza Soroushmehr +3
Wireless capsule endoscopy (WCE) is an effective means of diagnosis of gastrointestinal disorders. Detection of informative scenes by WCE could reduce the length of transmitted vid…
Lossless Image Compression Algorithm for Wireless Capsule Endoscopy by Content-Based Classification of Image Blocks
Atefe Rajaeefar, Ali Emami, S. M. Reza Soroushmehr +3
Recent advances in capsule endoscopy systems have introduced new methods and capabilities. The capsule endoscopy system, by observing the entire digestive tract, has significantly…
Classification of Informative Frames in Colonoscopy Videos Using Convolutional Neural Networks with Binarized Weights
Mojtaba Akbari, Majid Mohrekesh, Shima Rafiei +4
Colorectal cancer is one of the common cancers in the United States. Polyp is one of the main causes of the colonic cancer and early detection of polyps will increase chance of can…
Liver Segmentation in Abdominal CT Images by Adaptive 3D Region Growing
Shima Rafiei, Nader Karimi, Behzad Mirmahboub +4
Automatic liver segmentation plays an important role in computer-aided diagnosis and treatment. Manual segmentation of organs is a difficult and tedious task and so prone to human…
Deep Learning in Pharmacogenomics: From Gene Regulation to Patient Stratification
Alexandr A. Kalinin, Gerald A. Higgins, Narathip Reamaroon +5
This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: (1) identification of novel regulatory variants located in no…