activity
20072020
most citedEvaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANs

43 citations · 47 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2020★ 43 cited

Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANs

Bradley Segal, David M. Rubin, Grace Rubin +1

Chest x-rays are a vital tool in the workup of many patients. Similar to most medical imaging modalities, they are profoundly multi-modal and are capable of visualising a variety o…

cs.HC2020★ 2 cited

Addressing the eye-fixation problem in gaze tracking for human computer interface using the Vestibulo-ocular Reflex

Adam Pantanowitz, Kimoon Kim, Chelsey Chewins +2

A custom head-mounted system to track smooth eye movements for control of a mouse cursor is implemented and evaluated. The system comprises a head-mounted infrared camera, an infra…

cs.LG2019

Estimation of Body Mass Index from Photographs using Deep Convolutional Neural Networks

Adam Pantanowitz, Emmanuel Cohen, Philippe Gradidge +4

Obesity is an important concern in public health, and Body Mass Index is one of the useful (and proliferant) measures. We use Convolutional Neural Networks to determine Body Mass I…

cs.CV2007★ 1 cited

Automatic Detection of Pulmonary Embolism using Computational Intelligence

Simon Scurrell, Tshilidzi Marwala, David Rubin

This article describes the implementation of a system designed to automatically detect the presence of pulmonary embolism in lung scans. These images are firstly segmented, before…

cs.CV2007★ 1 cited

Enhancement of Noisy Planar Nuclear Medicine Images using Mean Field Annealing

D. L. Falk, D. M. Rubin, T. Marwala

Nuclear medicine (NM) images inherently suffer from large amounts of noise and blur. The purpose of this research is to reduce the noise and blur while maintaining image integrity…

cs.AI2007

An Adaptive Strategy for the Classification of G-Protein Coupled Receptors

S. Mohamed, D. Rubin, T. Marwala

One of the major problems in computational biology is the inability of existing classification models to incorporate expanding and new domain knowledge. This problem of static clas…