Downloads

Code for unsupervised multiple kernel learning (U-MKL) for dimensionality reduction

based on the work from:
Lin YY et al. IEEE T Pattern Anal Mach Intell 2011;33:1147-60.
Sanchez S et al. Med Image Anal 2017;35:70-82.

download here
(code + demo)


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Code for cardiac segmentation of MR images using spatial propagation

based on the work from:
Zheng Q et al. IEEE T Med Imaging, 2018.

download here
(Python code)


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Realistic synthetic cardiac MR sequences

based on the work from:
Duchateau N et al. IEEE T Med Imaging 2018;37:755-66.

download here
(synthetic sequences: meshes + images, from the STACOM 2011 challenge data)


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Material for the CARDIOFUNXION winter school 2018

(machine learning in cardiology)

data + instructions


Material for the USART summer school 2015

(machine learning in cardiac ultrasound)

based on the course from:
Ng A et al. Machine learning. Coursera, 2013.

data + instructions


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Code for multi-scale kernel regression

based on the work from:
Bermanis A et al. Appl Comput Harm Anal 2013;34:15-29.
Duchateau N et al. Proc. SEE-GSI, LNCS 2013;8085:578-86.

download here
(Matlab code)


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Code for the TDFFD tracking along image sequences

based on the work from:
De Craene M et al. Med Image Anal 2012;16:427-50.

download here
(ITK/C++ code)
De Craene M, Piella G. An implementation of TDFFD and LDFFD algorithms. Insight Journal, 2012.


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Code for the spatiotemporal alignment steps (cardiac motion or deformation atlas)

based on the work from:
Duchateau N et al. Med Image Anal 2011;15:316-28.
Duchateau N et al. Proc. STIA-MICCAI’12, LNCS 2012;7570:25-37.

download here
(Matlab code, generic, but data reading steps specific to GE-Echopac export)
[updated version: simpler code + fixed bugs (14/01/2014)]


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Statistical shape model of the full heart

based on the work from:
Hoogendoorn C et al. IEEE T Med Imaging 2013;32:28-44.

download here
(full heart or LV model, all phases or first phase, PCA or bilinear model)


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