4 citations · 4 across the 3 of their papers we have counts for
7 papers
Uncertainty guided semi-supervised segmentation of retinal layers in OCT images
Suman Sedai, Bhavna Antony, Ravneet Rai +5
Deep convolutional neural networks have shown outstanding performance in medical image segmentation tasks. The usual problem when training supervised deep learning methods is the l…
Analyzing Epistemic and Aleatoric Uncertainty for Drusen Segmentation in Optical Coherence Tomography Images
Tinu Theckel Joy, Suman Sedai, Rahil Garnavi
Age-related macular degeneration (AMD) is one of the leading causes of permanent vision loss in people aged over 60 years. Accurate segmentation of biomarkers such as drusen that p…
Dueling Deep Q-Network for Unsupervised Inter-frame Eye Movement Correction in Optical Coherence Tomography Volumes
Yasmeen M. George, Suman Sedai, Bhavna J. Antony +4
In optical coherence tomography (OCT) volumes of retina, the sequential acquisition of the individual slices makes this modality prone to motion artifacts, misalignments between ad…
Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning
Suman Sedai, Bhavna Antony, Dwarikanath Mahapatra +1
Optical coherence tomography (OCT) is commonly used to analyze retinal layers for assessment of ocular diseases. In this paper, we propose a method for retinal layer segmentation a…
Deep multiscale convolutional feature learning for weakly supervised localization of chest pathologies in X-ray images
Suman Sedai, Dwarikanath Mahapatra, Zongyuan Ge +2
Localization of chest pathologies in chest X-ray images is a challenging task because of their varying sizes and appearances. We propose a novel weakly supervised method to localiz…
Chest X-rays Classification: A Multi-Label and Fine-Grained Problem
Zongyuan Ge, Dwarikanath Mahapatra, Suman Sedai +2
The widely used ChestX-ray14 dataset addresses an important medical image classification problem and has the following caveats: 1) many lung pathologies are visually similar, 2) a…