A Segmentation Method of Foramen Ovale Based on Multiatlas
Author(s) -
Jiashi Zhao,
Huatao Ge,
Wei He,
Yanfang Li,
Weili Shi,
Zhengang Jiang,
Yonghui Li,
Xingzhi Li
Publication year - 2021
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2021/5221111
Subject(s) - foramen ovale (heart) , patent foramen ovale , medicine , trigeminal neuralgia , segmentation , skull , trigeminal nerve , computer science , radiology , artificial intelligence , surgery , percutaneous
Trigeminal neuralgia is a neurological disease. It is often treated by puncturing the trigeminal nerve through the skin and the oval foramen of the skull to selectively destroy the pain nerve. The process of puncture operation is difficult because the morphology of the foramen ovale in the skull base is varied and the surrounding anatomical structure is complex. Computer-aided puncture guidance technology is extremely valuable for the treatment of trigeminal neuralgia. Computer-aided guidance can help doctors determine the puncture target by accurately locating the foramen ovale in the skull base. Foramen ovale segmentation is a prerequisite for locating but is a tedious and error-prone task if done manually. In this paper, we present an image segmentation solution based on the multiatlas method that automatically segments the foramen ovale. We developed a data set of 30 CT scans containing 20 foramen ovale atlas and 10 CT scans for testing. Our approach can perform foramen ovale segmentation in puncture operation scenarios based solely on limited data. We propose to utilize this method as an enabler in clinical work.
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