11 citations · 20 across the 6 of their papers we have counts for
11 papers · 1 filter
Censor-aware Semi-supervised Learning for Survival Time Prediction from Medical Images
Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento +1
Survival time prediction from medical images is important for treatment planning, where accurate estimations can improve healthcare quality. One issue affecting the training of sur…
Post-hoc Overall Survival Time Prediction from Brain MRI
Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento +1
Overall survival (OS) time prediction is one of the most common estimates of the prognosis of gliomas and is used to design an appropriate treatment planning. State-of-the-art (SOT…
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…
Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy
Yu Tian, Gabriel Maicas, Leonardo Zorron Cheng Tao Pu +3
Anomaly detection methods generally target the learning of a normal image distribution (i.e., inliers showing healthy cases) and during testing, samples relatively far from the lea…
Region Proposals for Saliency Map Refinement for Weakly-supervised Disease Localisation and Classification
Renato Hermoza, Gabriel Maicas, Jacinto C. Nascimento +1
The deployment of automated systems to diagnose diseases from medical images is challenged by the requirement to localise the diagnosed diseases to justify or explain the classific…
Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT
Saskia Glaser, Gabriel Maicas, Sergei Bedrikovetski +2
The diagnosis of the presence of metastatic lymph nodes from abdominal computed tomography (CT) scans is an essential task performed by radiologists to guide radiation and chemothe…