Can I read Robust Prototypical Few-Shot Organ Segmentation With Regularized Neural-ODEs on EtoBox?

Robust Prototypical Few-Shot Organ Segmentation With Regularized Neural-ODEs by Prashant Pandey; Mustafa Chasmai; Tanuj Sur; Brejesh Lall is a Medicine article available to read on EtoBox.

What is Robust Prototypical Few-Shot Organ Segmentation With Regularized Neural-ODEs about?

Despite the tremendous progress made by deep learning models in image semantic segmentation, they typically require large annotated examples, and increasing attention is being diverted to problem settings like Few-Shot Learning (FSL) where only a small amount of annotation is needed for generalisation to novel classes. This is especially seen in medical domains where dense pixel-level annotations are expensive to obtain. In this paper, we propose Regularized Prototypical Neural Ordinary Differential Equation (R-PNODE), a method that leverages intrinsic properties of Neural-ODEs, assisted and enhanced by additional cluster and consistency losses to perform Few-Shot Segmentation (FSS) of organs. R-PNODE constrains support and query features from the same classes to lie closer in the representation space thereby improving the performance over the existing Convolutional Neural Network (CNN) based FSS methods. We further demonstrate that while many existing Deep CNN-based methods tend to be extremely vulnerable to adversarial attacks, R-PNODE exhibits increased adversarial robustness for a wide array of these attacks. We experiment with three publicly available multi-organ segmentation

Who reads Robust Prototypical Few-Shot Organ Segmentation With Regularized Neural-ODEs?

Author

Prashant Pandey; Mustafa Chasmai; Tanuj Sur; Brejesh Lall

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2023

Language

EN

Field

Medicine (Health Sciences)