Match!
Timothy F. Cootes
University of Manchester
308Publications
64H-index
28.9kCitations
Publications 308
Newest
#1Riccardo Storchi (University of Manchester)H-Index: 10
#2Jessica Rodgers (University of Manchester)H-Index: 1
Last.Robert J. Lucas (University of Manchester)H-Index: 43
view all 10 authors...
Measuring vision in rodents is a critical step for understanding vision, improving models of human disease, and developing therapies. Established behavioural tests for perceptual vision, such as the visual water task, rely on learning. The learning process, while effective for sighted animals, can be laborious and stressful in animals with impaired vision, requiring long periods of training. Current tests that that do not require training are based on sub-conscious, reflex responses (e.g. optoki...
#1W.P. GielisH-Index: 2
#2Harrie Weinans (TU Delft: Delft University of Technology)H-Index: 65
Last.Claudia Lindner (University of Manchester)H-Index: 10
view all 8 authors...
Summary Objective To design an automated workflow for hip radiographs focused on joint shape and tests its prognostic value for future hip osteoarthritis. Design We used baseline and eight-year follow-up data from 1002 participants of the CHECK-study. The primary outcome was definite radiographic hip osteoarthritis (rHOA) (Kellgren-Lawrence grade ≥2 or joint replacement) at eight-year follow-up. We designed a method to automatically segment the hip joint from radiographs. Subsequently, we applie...
#1Thomas A. Perry (MAHSC: Manchester Academic Health Science Centre)H-Index: 1
#2A. D. Gait (University of Manchester)H-Index: 7
Last.Timothy F. Cootes (University of Manchester)H-Index: 64
view all 9 authors...
© 2019 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. Purpose: Synovitis is common in knee osteoarthritis and is associated with both knee pain and progression of disease. Semiautomated methods have been developed for quantitative assessment of structure in knee osteoarthritis. Our aims were to apply a novel semiautomated assessment method using 3D active appearance modeling for the quantifica...
#1Luca Minciullo (University of Manchester)H-Index: 2
#2Matthew J. ParkesH-Index: 11
Last.Timothy F. CootesH-Index: 64
view all 4 authors...
Objectives The relationship between radiographic evidence of osteoarthritis and knee pain has been weak. This may be because features that best discriminate knees with pain have not been included in analyses. We tested the correlation between knee pain and radiographic features taking into account both image analysis features and manual scores. Methods Using data of the Multicentre Osteoarthritis Study, we tested in a cross-sectional design how well X-ray features discriminated those with freque...
Sep 17, 2018 in MICCAI (Medical Image Computing and Computer-Assisted Intervention)
#1Nicolás Vila Blanco (University of Santiago de Compostela)H-Index: 1
#2Timothy F. Cootes (University of Manchester)H-Index: 64
Last.M. J. Carreira (University of Santiago de Compostela)H-Index: 10
view all 5 authors...
This work addresses the problem of segmenting teeth in panoramic dental images. Random forest regression voting constrained local models were applied firstly to locate the mandible and the approximate pose of each tooth, and secondly to locate the full outline of each individual tooth. An automatically computed quality-of-fit measure was proposed to identify missing teeth. The system was evaluated using 346 manually annotated images containing adult-stage mandibular teeth. Encouraging results we...
Sep 16, 2018 in MICCAI (Medical Image Computing and Computer-Assisted Intervention)
#1Adrian K. Davison (University of Manchester)H-Index: 7
#2Claudia Lindner (University of Manchester)H-Index: 10
Last.Timothy F. Cootes (University of Manchester)H-Index: 64
view all 6 authors...
We propose a new method for fully automatic landmark localisation using Convolutional Neural Networks (CNNs). Training a CNN to estimate a Gaussian response (“heatmap”) around each target point is known to be effective for this task. We show that better results can be obtained by training a CNN to predict the offset to the target point at every location, then using these predictions to vote for the point position. We show the advantages of the approach, including those of using a novel loss func...
12345678910