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Cylindrical Transform: 3D Semantic Segmentation of Kidneys With Limited Annotated Images
The images generated from a cylindrical transform augment a limited annotated set of images in three dimensions.
Recent Advances in Recurrent Neural Networks
Recurrent neural networks (RNNs) are capable of learning features and long term dependencies from sequential and time-series data.
Generalization of Deep Neural Networks for Chest Pathology Classification in X-Rays Using Generative Adversarial Networks
Medical datasets are often highly imbalanced with over-representation of common medical problems and a paucity of data from rare conditions.
Interpretation of Mammogram and Chest X-Ray Reports Using Deep Neural Networks - Preliminary Results
Radiology reports are an important means of communication between radiologists and other physicians.
Image Augmentation using Radial Transform for Training Deep Neural Networks
We propose a sampling method based on the radial transform in a polar coordinate system for image augmentation to facilitate the training of deep learning models from limited source data.
A Convolutional Neural Network for Search Term Detection
Pathfinding in hospitals is challenging for patients, visitors, and even employees.
