39 citations · 205 across the 13 of their papers we have counts for
34 papers
TorchXRayVision: A library of chest X-ray datasets and models
Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin +8
TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models. It provides a common interface and common pre-processing chain fo…
Benefits of Linear Conditioning with Metadata for Image Segmentation
Andreanne Lemay, Charley Gros, Olivier Vincent +3
Medical images are often accompanied by metadata describing the image (vendor, acquisition parameters) and the patient (disease type or severity, demographics, genomics). This meta…
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays
Joseph Paul Cohen, Rupert Brooks, Sovann En +4
Motivation: Traditional image attribution methods struggle to satisfactorily explain predictions of neural networks. Prediction explanation is important, especially in medical imag…
ivadomed: A Medical Imaging Deep Learning Toolbox
Charley Gros, Andreanne Lemay, Olivier Vincent +4
ivadomed is an open-source Python package for designing, end-to-end training, and evaluating deep learning models applied to medical imaging data. The package includes APIs, comman…
A Benchmark of Medical Out of Distribution Detection
Tianshi Cao, Chin-Wei Huang, David Yu-Tung Hui +1
Motivation: Deep learning models deployed for use on medical tasks can be equipped with Out-of-Distribution Detection (OoDD) methods in order to avoid erroneous predictions. Howeve…
Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Prediction
Hasib Zunair, Aimon Rahman, Nabeel Mohammed +1
A common approach to medical image analysis on volumetric data uses deep 2D convolutional neural networks (CNNs). This is largely attributed to the challenges imposed by the nature…