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A variant of the level set method and applications to image segmentation

Mathematics of computation, 2006-07, Vol.75 (255), p.1155-1174

2006

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Imaging, Vision and Learning Based on Optimization and PDEs: IVLOPDE, Bergen, Norway, August 29 - September 2, 2016

1st ed. 2018., 2018

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Energy Minimization Methods in Computer Vision and Pattern Recognition: 10th International Conference, EMMCVPR 2015, Hong Kong, China, January 13-16, 2015. Proceedings

1, 2015

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Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional

International journal of computer vision, 2006-01, Vol.66 (1), p.5-18

2006

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Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time

IEEE transactions on image processing, 2003-12, Vol.12 (12), p.1579-1590

2003

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Volltext

A binary level set model and some applications to Mumford-Shah image segmentation

IEEE transactions on image processing, 2006-05, Vol.15 (5), p.1171-1181

2006

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Volltext

Computing Ischemic Regions in the Heart With the Bidomain Model-First Steps Towards Validation

IEEE transactions on medical imaging, 2013-06, Vol.32 (6), p.1085-1096

2013

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Volltext

Noise removal using smoothed normals and surface fitting

IEEE transactions on image processing, 2004-10, Vol.13 (10), p.1345-1357

2004

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Volltext

Level set method for positron emission tomography

International journal of biomedical imaging, 2007, Vol.2007, p.26950-26950

2007

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Human behaviour modelling for welfare technology using hidden Markov models

Pattern recognition letters, 2020-09, Vol.137, p.71-79

2020

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Imaging, Vision and Learning Based on Optimization and PDEs: IVLOPDE, Bergen, Norway, August 29 – September 2, 2016

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On the use of the resting potential and level set methods for identifying ischemic heart disease: An inverse problem

Journal of computational physics, 2007-01, Vol.220 (2), p.772-790

2007

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A Computationally Efficient Method for Determining the Size and Location of Myocardial Ischemia

IEEE transactions on biomedical engineering, 2009-02, Vol.56 (2), p.263-272

2009

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Volltext

Processing of high-speed videos of shock wave boundary layer interactions

Signal, image and video processing, 2021-04, Vol.15 (3), p.607-615

2021

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On the possibility for computing the transmembrane potential in the heart with a one shot method: An inverse problem

Mathematical biosciences, 2007-12, Vol.210 (2), p.523-553

2007

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Piecewise Constant Level Set Methods and Image Segmentation

Lecture notes in computer science, 2005, p.573-584

2005

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Computing the size and location of myocardial ischemia using measurements of ST-segment shift

IEEE transactions on biomedical engineering, 2006-06, Vol.53 (6), p.1024-1031

2006

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An Image Processing Framework for Automatic Tracking of Wave Fronts and Estimation of Wave Front Velocity for a Gas Experiment

Representations, Analysis and Recognition of Shape and Motion from Imaging Data, p.45-55

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Scale Space and Variational Methods in Computer Vision: Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings

2009 edition, 2009

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A linear system of partial differential equations modeling the resting potential of a heart with regional ischemia

Mathematical biosciences, 2007-11, Vol.210 (1), p.238-252

2007

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Bidomain simulations of subendocardial ischemia: The forward and inverse problems

Computing in Cardiology 2014, 2014, p.1149-1152

2014

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Part IV Machine Learning and Big Data Analysis

Imaging, Vision and Learning Based on Optimization and PDEs, 2018

2018

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Intro

Imaging, Vision and Learning Based on Optimization and PDEs, 2018

2018

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Part II Image Enhancement, Restoration and Registration

Imaging, Vision and Learning Based on Optimization and PDEs, 2018

2018

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Part III 3D Image Understanding and Classification

Imaging, Vision and Learning Based on Optimization and PDEs, 2018

2018

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A variant of the level set method and applications to image segmentation

Imaging, Vision and Learning Based on Optimization and PDEs: IVLOPDE, Bergen, Norway, August 29 - September 2, 2016

Energy Minimization Methods in Computer Vision and Pattern Recognition: 10th International Conference, EMMCVPR 2015, Hong Kong, China, January 13-16, 2015. Proceedings

Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional

Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time

A binary level set model and some applications to Mumford-Shah image segmentation

Computing Ischemic Regions in the Heart With the Bidomain Model-First Steps Towards Validation

Noise removal using smoothed normals and surface fitting

Level set method for positron emission tomography

Human behaviour modelling for welfare technology using hidden Markov models

Imaging, Vision and Learning Based on Optimization and PDEs: IVLOPDE, Bergen, Norway, August 29 – September 2, 2016

On the use of the resting potential and level set methods for identifying ischemic heart disease: An inverse problem

A Computationally Efficient Method for Determining the Size and Location of Myocardial Ischemia

Processing of high-speed videos of shock wave boundary layer interactions

On the possibility for computing the transmembrane potential in the heart with a one shot method: An inverse problem

Piecewise Constant Level Set Methods and Image Segmentation

Computing the size and location of myocardial ischemia using measurements of ST-segment shift

An Image Processing Framework for Automatic Tracking of Wave Fronts and Estimation of Wave Front Velocity for a Gas Experiment

Scale Space and Variational Methods in Computer Vision: Second International Conference, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings

A linear system of partial differential equations modeling the resting potential of a heart with regional ischemia

Bidomain simulations of subendocardial ischemia: The forward and inverse problems

Part IV Machine Learning and Big Data Analysis

Intro

Part II Image Enhancement, Restoration and Registration

Part III 3D Image Understanding and Classification

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