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3D segmentation of the whole heart vasculature using improved multi-threshold Otsu and white top-hat scale space hessian based vessel filter

Bukenya, Faiza; Ehling, Josef; Kalema, Abdu Kiweewa; Eyoh, Imo; Robert, John; Bai, Li

3D segmentation of the whole heart vasculature using improved multi-threshold Otsu and white top-hat scale space hessian based vessel filter Thumbnail


Authors

Faiza Bukenya

Josef Ehling

Abdu Kiweewa Kalema

Imo Eyoh

John Robert

Li Bai



Abstract

Quantification of vessel density helps to know the stage of the disease during diagnosis and patient's response to treatment. However, this requires presence of all vessels in the image. The available segmentation techniques that are manual based are prone to errors, tiresome and slow, while some that are automated do face difficulty in distinguishing the vessel tissue from the non-vessel tissue due to the presence of intensity inhomogeneity and noise in images. Therefore, there is need for improved segmentation methods that can extract all sizes of vessels for better quantification of the vessel density and improved decision making during diagnosis. In this paper, a 3D hybrid approach for segmentation has been developed, based on white top hat scale space hessian vessel enhancement filter and multi-threshold Otsu method. The hybrid method can address the intensity inhomogeneity, as a result, more vessels of different sizes are detected. The method is also robust and able to detect abnormalities in the vessels.

Citation

Bukenya, F., Ehling, J., Kalema, A. K., Eyoh, I., Robert, J., & Bai, L. (2016). 3D segmentation of the whole heart vasculature using improved multi-threshold Otsu and white top-hat scale space hessian based vessel filter. In Proceedings - 2016 IEEE Symposium Series on Computational Intelligence (SSCI) (1-7). https://doi.org/10.1109/SSCI.2016.7850137

Conference Name 2016 IEEE Symposium Series on Computational Intelligence (SSCI)
Conference Location Athens, Greece
Start Date Dec 6, 2016
End Date Dec 9, 2016
Acceptance Date Oct 31, 2016
Online Publication Date Feb 13, 2017
Publication Date 2016-12
Deposit Date Aug 5, 2020
Publicly Available Date Mar 28, 2024
Publisher Institute of Electrical and Electronics Engineers
Pages 1-7
Book Title Proceedings - 2016 IEEE Symposium Series on Computational Intelligence (SSCI)
ISBN 978-1-5090-4241-8
DOI https://doi.org/10.1109/SSCI.2016.7850137
Public URL https://nottingham-repository.worktribe.com/output/4812320
Publisher URL https://ieeexplore.ieee.org/abstract/document/7850137
Additional Information © 2017 IEEE.Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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