3 papers
cs.CV2022
Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology
Pranav Agnihotri, Sara Ketabi, Khashayar +2
Traditional datasets for the radiological diagnosis tend to only provide the radiology image alongside the radiology report. However, radiology reading as performed by radiologists…
eess.IV2022
Improving Disease Classification Performance and Explainability of Deep Learning Models in Radiology with Heatmap Generators
Akino Watanabe, Sara Ketabi, Khashayar +2
As deep learning is widely used in the radiology field, the explainability of such models is increasingly becoming essential to gain clinicians' trust when using the models for dia…
cs.CV2020
Data Augmentation using Generative Adversarial Networks (GANs) for GAN-based Detection of Pneumonia and COVID-19 in Chest X-ray Images
Saman Motamed, Patrik Rogalla, Farzad Khalvati
Successful training of convolutional neural networks (CNNs) requires a substantial amount of data. With small datasets networks generalize poorly. Data Augmentation techniques impr…