Expected Label Value (ELV) for Image Segmentation

Versión 1.1.1 (15,1 KB) por Iman Aganj

Supervised image soft-segmentation using the multi-atlas based Expected Label Value (ELV) approach.

https://www.nitrc.org/projects/elv

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This is the public Matlab implementation of medical image soft segmentation using the supervised multi-atlas based Expected Label Value (ELV) approach proposed by Aganj and Fischl (IEEE TMI 2021). This approach considers the probability of all possible atlas-to-image transformations and computes the ELV, thus bypassing deformable registration and avoiding the associated computational costs. A short tutorial is included in EXAMPLE.m.

This package also includes functions for FFT-based convolution, which can be used independently.

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Iman Aganj (2024). Expected Label Value (ELV) for Image Segmentation (https://www.mathworks.com/matlabcentral/fileexchange/81283-expected-label-value-elv-for-image-segmentation), MATLAB Central File Exchange. Recuperado 26 julio, 2024.

Aganj, Iman, and Bruce Fischl. “Multi-Atlas Image Soft Segmentation via Computation of the Expected Label Value.” IEEE Transactions on Medical Imaging, vol. 40, no. 6, Institute of Electrical and Electronics Engineers (IEEE), June 2021, pp. 1702–10, doi:10.1109/tmi.2021.3064661.

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Compatibilidad con la versión de MATLAB

Se creó con R2020b

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Inspirado por: Mid-Space-Independent and IDIR Deformable Image Registration

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Versión	Publicado	Notas de la versión
1.1.1	1 dic 2023	Adding a missing file (sizeD.m).	Descargar
1.1.0	1 may 2023	ELV segmentation has been extended to accept multi-channel images.	Descargar
1.0.4	2 jun 2021	Minor update.	Descargar
1.0.3	25 ene 2021	The IBSR example has been updated.	Descargar
1.0.2	22 oct 2020	Minor update.	Descargar
1.0.1	16 oct 2020	Minor update.	Descargar
1.0.0	16 oct 2020		Descargar

MLA	Aganj, Iman, and Bruce Fischl. “Multi-Atlas Image Soft Segmentation via Computation of the Expected Label Value.” IEEE Transactions on Medical Imaging, vol. 40, no. 6, Institute of Electrical and Electronics Engineers (IEEE), June 2021, pp. 1702–10, doi:10.1109/tmi.2021.3064661.
APA	Aganj, I., & Fischl, B. (2021). Multi-Atlas Image Soft Segmentation via Computation of the Expected Label Value. IEEE Transactions on Medical Imaging, 40(6), 1702–1710. Institute of Electrical and Electronics Engineers (IEEE). Retrieved from https://doi.org/10.1109%2Ftmi.2021.3064661
BibTeX	@article{Aganj_2021, doi = {10.1109/tmi.2021.3064661}, url = {https://doi.org/10.1109%2Ftmi.2021.3064661}, year = 2021, month = {jun}, publisher = {Institute of Electrical and Electronics Engineers ({IEEE})}, volume = {40}, number = {6}, pages = {1702--1710}, author = {Iman Aganj and Bruce Fischl}, title = {Multi-Atlas Image Soft Segmentation via Computation of the Expected Label Value}, journal = {{IEEE} Transactions on Medical Imaging} }