10 Result(s)
within
Tim F. Cootes
Computer Graphics
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Chapter and Conference Paper
Small Defect Detection Using Convolutional Neural Network Features and Random Forests
We address the problem of identifying small abnormalities in an imaged region, important in applications such as industrial inspection. The goal is to label the pixels corresponding to a defect with a minimum ...
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Chapter and Conference Paper
Learning-Based Shape Model Matching: Training Accurate Models with Minimal Manual Input
Recent work has shown that statistical model-based methods lead to accurate and robust results when applied to the segmentation of bone shapes from radiographs. To achieve good performance, model-based matchin...
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Chapter and Conference Paper
Accurate Bone Segmentation in 2D Radiographs Using Fully Automatic Shape Model Matching Based On Regression-Voting
Recent work has shown that using Random Forests (RFs) to vote for the optimal position of model feature points leads to robust and accurate shape model matching. This paper applies RF regression-voting as part...
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Chapter and Conference Paper
Robust and Accurate Shape Model Fitting Using Random Forest Regression Voting
A widely used approach for locating points on deformable objects is to generate feature response images for each point, then to fit a shape model to the response images. We demonstrate that Random Forest regre...
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Chapter and Conference Paper
Deformable Object Modelling and Matching
Statistical models of the shape and appearance of deformable objects have become widely used in Computer Vision and Medical Image Analysis. Here we give an overview of such models and of two efficient algorith...
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Chapter and Conference Paper
3D Brain Segmentation Using Active Appearance Models and Local Regressors
We describe an efficient and accurate method for segmenting sets of subcortical structures in 3D MR images of the brain. We first find the approximate position of all the structures using a global Active Appea...
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Chapter and Conference Paper
Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI
The automation of segmentation of medical images is an active research area. However, there has been criticism of the standard of evaluation of methods. We have comprehensively evaluated four novel methods of ...
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Chapter and Conference Paper
Shape Discrimination in the Hippocampus Using an MDL Model
We extend recent work on building 3D statistical shape models, automatically, from sets of training shapes and describe an application in shape analysis. Using an existing measure of model quality, based on a ...
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Chapter and Conference Paper
3D Statistical Shape Models Using Direct Optimisation of Description Length
We describe an automatic method for building optimal 3D statistical shape models from sets of training shapes. Although shape models show considerable promise as a basis for segmenting and interpreting images,...
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Chapter and Conference Paper
Locating Overlap** Flexible Shapes Using Geometrical Constraints
In an earlier paper [1] we have proposed a shape representation called the CLD (Chord Length Distribution) which possesses many of the often-quoted desirable properties of a shape representation. It also captu...
