3 citations · 7 across the 5 of their papers we have counts for
5 papers
Fully Convolutional Neural Network for Semantic Segmentation of Anatomical Structure and Pathologies in Colour Fundus Images Associated with Diabetic Retinopathy
Oindrila Saha, Rachana Sathish, Debdoot Sheet
Diabetic retinopathy (DR) is the most common form of diabetic eye disease. Retinopathy can affect all diabetic patients and becomes particularly dangerous, increasing the risk of b…
Segmentation of Lumen and External Elastic Laminae in Intravascular Ultrasound Images using Ultrasonic Backscattering Physics Initialized Multiscale Random Walks
Debarghya China, Pabitra Mitra, Debdoot Sheet
Coronary artery disease accounts for a large number of deaths across the world and clinicians generally prefer using x-ray computed tomography or magnetic resonance imaging for loc…
SUMNet: Fully Convolutional Model for Fast Segmentation of Anatomical Structures in Ultrasound Volumes
Sumanth Nandamuri, Debarghya China, Pabitra Mitra +1
Ultrasound imaging is generally employed for real-time investigation of internal anatomy of the human body for disease identification. Delineation of the anatomical boundary of org…
Learning a Deep Convolution Network with Turing Test Adversaries for Microscopy Image Super Resolution
Francis Tom, Himanshu Sharma, Dheeraj Mundhra +2
Adversarially trained deep neural networks have significantly improved performance of single image super resolution, by hallucinating photorealistic local textures, thereby greatly…
UltraCompression: Framework for High Density Compression of Ultrasound Volumes using Physics Modeling Deep Neural Networks
Debarghya China, Francis Tom, Sumanth Nandamuri +4
Ultrasound image compression by preserving speckle-based key information is a challenging task. In this paper, we introduce an ultrasound image compression framework with the abili…