47 citations · 119 across the 36 of their papers we have counts for
8 papers · 1 filter
Liver Segmentation from Multimodal Images using HED-Mask R-CNN
Supriti Mulay, Deepika G, Jeevakala S +2
Precise segmentation of the liver is critical for computer-aided diagnosis such as pre-evaluation of the liver for living donor-based transplantation surgery. This task is challeng…
Recon-GLGAN: A Global-Local context based Generative Adversarial Network for MRI Reconstruction
Balamurali Murugesan, Vijaya Raghavan S, Kaushik Sarveswaran +2
Magnetic resonance imaging (MRI) is one of the best medical imaging modalities as it offers excellent spatial resolution and soft-tissue contrast. But, the usage of MRI is limited…
Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana +3
For the task of medical image segmentation, fully convolutional network (FCN) based architectures have been extensively used with various modifications. A rising trend in these arc…
Deep Network for Capacitive ECG Denoising
Vignesh Ravichandran, Balamurali Murugesan, Sharath M Shankaranarayana +4
Continuous monitoring of cardiac health under free living condition is crucial to provide effective care for patients undergoing post operative recovery and individuals with high c…
RespNet: A deep learning model for extraction of respiration from photoplethysmogram
Vignesh Ravichandran, Balamurali Murugesan, Vaishali Balakarthikeyan +5
Respiratory ailments afflict a wide range of people and manifests itself through conditions like asthma and sleep apnea. Continuous monitoring of chronic respiratory ailments is se…
Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation
Sharath M Shankaranarayana, Keerthi Ram, Kaushik Mitra +1
Glaucoma is a serious ocular disorder for which the screening and diagnosis are carried out by the examination of the optic nerve head (ONH). The color fundus image (CFI) is the mo…
Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana +2
Image segmentation is a primary task in many medical applications. Recently, many deep networks derived from U-Net have been extensively used in various medical image segmentation…
Joint shape learning and segmentation for medical images using a minimalistic deep network
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana +2
Recently, state-of-the-art results have been achieved in semantic segmentation using fully convolutional networks (FCNs). Most of these networks employ encoder-decoder style archit…