Search Results for author:
Found 4 papers, 2 papers with code
Prototype Learning for Explainable Brain Age Prediction
Therefore, in this work, we present ExPeRT: an explainable prototype-based model specifically designed for regression tasks.
INSightR-Net: Interpretable Neural Network for Regression using Similarity-based Comparisons to Prototypical Examples
Convolutional neural networks (CNNs) have shown exceptional performance for a range of medical imaging tasks.
Primary Tumor Origin Classification of Lung Nodules in Spectral CT using Transfer Learning
Therefore, we propose a detection and classification system for lung nodules in CT scans.
Intensity augmentation for domain transfer of whole breast segmentation in MRI
Our results show that using intensity augmentation in addition to geometric augmentation is a suitable method to overcome the intensity domain shift and we expect it to be useful for a wide range of segmentation tasks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
