Expected Label Value (ELV) for Image Segmentation

Version 1.1.1 (15,1 KB) von 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.

Zitieren als

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. Abgerufen 27. Juli 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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Erstellt mit R2020b

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Inspiriert von: Mid-Space-Independent and IDIR Deformable Image Registration

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Version	Veröffentlicht	Versionshinweise
1.1.1	1. Dez 2023	Adding a missing file (sizeD.m).	Herunterladen
1.1.0	1. Mai 2023	ELV segmentation has been extended to accept multi-channel images.	Herunterladen
1.0.4	2. Jun 2021	Minor update.	Herunterladen
1.0.3	25. Jan 2021	The IBSR example has been updated.	Herunterladen
1.0.2	22. Okt 2020	Minor update.	Herunterladen
1.0.1	16. Okt 2020	Minor update.	Herunterladen
1.0.0	16. Okt 2020		Herunterladen

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} }