Towards developing a segmentation method for cerebral aneurysm using a statistical multiresolution approach

Egyptian Journal of Neurosurgery

Research

Yousra Regaya¹  Abbes Amira²  Sarada Prasad Dakua³ 

[1] College of Engineering, Qatar University, 2713, Doha, Qatar;School of Computer Science and Informatics, De Montfort University, LE1 9BH, Leicester, UK;Surgery, Hamad General Hospital, Hamad Medical Corporation, 3050, Doha, Qatar;

关键词: Cerebral aneurysm;    Segmentation;    Multiresolution analysis;    3D Rotational angiography;   

DOI  :  10.1186/s41984-023-00213-0

 received in 2022-11-01, accepted in 2023-01-10,  发布年份 2023

来源: Springer

【 摘 要 】

The computer aided diagnosis (CAD) algorithms are considered crucial during the treatment planning of cerebral aneurysms (CA), where segmentation is the first and foremost step. This paper presents a segmentation algorithm in two-dimensional domain combining a multiresolution and a statistical approach. Precisely, Contourlet transform (CT) extracts the image features, while Hidden Markov Random Field with Expectation Maximization (HMRF-EM) segments the image, based on the spatial contextual constraints. The proposed algorithm is tested on Three-Dimensional Rotational Angiography (3DRA) datasets; the average values of accuracy, DSC, FPR, FNR, specificity, and sensitivity, are found to be 99.64%, 92.44%, 0.09%, 5.81%, 99.84%, and 93.22%, respectively. Both qualitative and quantitative results obtained show the potential of the proposed method.

【 授权许可】

CC BY   
© The Author(s) 2023

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