38 citations · 43 across the 3 of their papers we have counts for
6 papers · 1 filter
Stack of discriminative autoencoders for multiclass anomaly detection in endoscopy images
Mohammad Reza Mohebbian, Khan A. Wahid, Paul Babyn
Wireless Capsule Endoscopy (WCE) helps physicians examine the gastrointestinal (GI) tract noninvasively. There are few studies that address pathological assessment of endoscopy ima…
Distance Metric-Based Learning with Interpolated Latent Features for Location Classification in Endoscopy Image and Video
Mohammad Reza Mohebbian, Khan A. Wahid, Anh Dinh +1
Conventional Endoscopy (CE) and Wireless Capsule Endoscopy (WCE) are known tools for diagnosing gastrointestinal (GI) tract disorders. Detecting the anatomical location of GI tract…
Automatic classification of multiple catheters in neonatal radiographs with deep learning
Robert D. E. Henderson, Xin Yi, Scott J. Adams +1
We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using…
Generative Adversarial Network in Medical Imaging: A Review
Xin Yi, Ekta Walia, Paul Babyn
Generative adversarial networks have gained a lot of attention in the computer vision community due to their capability of data generation without explicitly modelling the probabil…
Automatic catheter detection in pediatric X-ray images using a scale-recurrent network and synthetic data
Xin Yi, Scott Adams, Paul Babyn +1
Catheters are commonly inserted life supporting devices. X-ray images are used to assess the position of a catheter immediately after placement as serious complications can arise f…
Unsupervised and semi-supervised learning with Categorical Generative Adversarial Networks assisted by Wasserstein distance for dermoscopy image Classification
Xin Yi, Ekta Walia, Paul Babyn
Melanoma is a curable aggressive skin cancer if detected early. Typically, the diagnosis involves initial screening with subsequent biopsy and histopathological examination if nece…