26 citations · 47 across the 5 of their papers we have counts for
8 papers · 1 filter
CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification
Zhibin Liao, Kewen Liao, Haifeng Shen +6
Convolutional neural networks (CNNs) have gained significant popularity in orthopedic imaging in recent years due to their ability to solve fracture classification problems. A comm…
Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection
Yu Tian, Guansong Pang, Fengbei Liu +5
Current polyp detection methods from colonoscopy videos use exclusively normal (i.e., healthy) training images, which i) ignore the importance of temporal information in consecutiv…
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images
Yu Tian, Guansong Pang, Fengbei Liu +5
Unsupervised anomaly detection (UAD) learns one-class classifiers exclusively with normal (i.e., healthy) images to detect any abnormal (i.e., unhealthy) samples that do not confor…
Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning
Yu Tian, Leonardo Zorron Cheng Tao Pu, Yuyuan Liu +6
In this paper, we propose and analyse a system that can automatically detect, localise and classify polyps from colonoscopy videos. The detection of frames with polyps is formulate…
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning
Yu Tian, Guansong Pang, Yuanhong Chen +3
Anomaly detection with weakly supervised video-level labels is typically formulated as a multiple instance learning (MIL) problem, in which we aim to identify snippets containing a…
Pairwise Relation Learning for Semi-supervised Gland Segmentation
Yutong Xie, Jianpeng Zhang, Zhibin Liao +3
Accurate and automated gland segmentation on histology tissue images is an essential but challenging task in the computer-aided diagnosis of adenocarcinoma. Despite their prevalenc…