47 citations · 151 across the 18 of their papers we have counts for
15 papers · 1 filter
Probabilistic Integration of Object Level Annotations in Chest X-ray Classification
Tom van Sonsbeek, Xiantong Zhen, Dwarikanath Mahapatra +1
Medical image datasets and their annotations are not growing as fast as their equivalents in the general domain. This makes translation from the newest, more data-intensive methods…
Anomaly Detection in Retinal Images using Multi-Scale Deep Feature Sparse Coding
Sourya Dipta Das, Saikat Dutta, Nisarg A. Shah +2
Convolutional Neural Network models have successfully detected retinal illness from optical coherence tomography (OCT) and fundus images. These CNN models frequently rely on vast a…
Relational Subsets Knowledge Distillation for Long-tailed Retinal Diseases Recognition
Lie Ju, Xin Wang, Lin Wang +5
In the real world, medical datasets often exhibit a long-tailed data distribution (i.e., a few classes occupy most of the data, while most classes have rarely few samples), which r…
Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation
Dwarikanath Mahapatra
In supervised learning for medical image analysis, sample selection methodologies are fundamental to attain optimum system performance promptly and with minimal expert interactions…
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation
Lie Ju, Xin Wang, Lin Wang +6
Deep neural networks are known to be data-driven and label noise can have a marked impact on model performance. Recent studies have shown great robustness to classic image recognit…
AMD Severity Prediction And Explainability Using Image Registration And Deep Embedded Clustering
Dwarikanath Mahapatra
We propose a method to predict severity of age related macular degeneration (AMD) from input optical coherence tomography (OCT) images. Although there is no standard clinical sever…