214 citations · 450 across the 14 of their papers we have counts for
6 papers · 1 filter
How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis
Maria J. M. Chuquicusma, Sarfaraz Hussein, Jeremy Burt +1
Discriminating lung nodules as malignant or benign is still an underlying challenge. To address this challenge, radiologists need computer aided diagnosis (CAD) systems which can a…
Simultaneous Detection and Quantification of Retinal Fluid with Deep Learning
Dustin Morley, Hassan Foroosh, Saad Shaikh +1
We propose a new deep learning approach for automatic detection and segmentation of fluid within retinal OCT images. The proposed framework utilizes both ResNet and Encoder-Decoder…
Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT
Aliasghar Mortazi, Jeremy Burt, Ulas Bagci
Non-invasive detection of cardiovascular disorders from radiology scans requires quantitative image analysis of the heart and its substructures. There are well-established measurem…
CardiacNET: Segmentation of Left Atrium and Proximal Pulmonary Veins from MRI Using Multi-View CNN
Aliasghar Mortazi, Rashed Karim, Kawal Rhode +2
Anatomical and biophysical modeling of left atrium (LA) and proximal pulmonary veins (PPVs) is important for clinical management of several cardiac diseases. Magnetic resonance ima…
Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning
Sarfaraz Hussein, Kunlin Cao, Qi Song +1
Risk stratification of lung nodules is a task of primary importance in lung cancer diagnosis. Any improvement in robust and accurate nodule characterization can assist in identifyi…
TumorNet: Lung Nodule Characterization Using Multi-View Convolutional Neural Network with Gaussian Process
Sarfaraz Hussein, Robert Gillies, Kunlin Cao +2
Characterization of lung nodules as benign or malignant is one of the most important tasks in lung cancer diagnosis, staging and treatment planning. While the variation in the appe…