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ORIGINAL RESEARCH article
Front. Neurol.
Sec. Artificial Intelligence in Neurology
Volume 15 - 2024 |
doi: 10.3389/fneur.2024.1396513
This article is part of the Research Topic Exploring the Future of Neurology: How AI is Revolutionizing Diagnoses, Treatments, and Beyond View all 7 articles
Intelligent Analysis and Measurement of Semicircular Canal Spatial Attitude
Provisionally accepted- 1 Third Affiliated Hospital, School of Medicine, Shanghai University, Shanghai, 200444, shanghai, China
- 2 Third Affiliated Hospital of Shanghai University, Wenzhou Third Clinical Institute Affiliated to Wenzhou Medical University, Wenzhou People’s Hospital, Wenzhou, China,325000, Wenzhou, China
Objective: The primary aim of this investigation was to devise an intelligent approach for interpreting and measuring the spatial orientation of semicircular canals based on cranial MRI. The ultimate objective is to employ this intelligent method to construct a precise mathematical model that accurately represents the spatial orientation of the semicircular canals.Methods: Using a dataset of 115 cranial MRI scans, this study employed the nnDetection deep learning algorithm to perform automated segmentation of the semicircular canals and the eyeballs (left and right). The center points of each semicircular canal were organized into an ordered structure using point characteristic analysis. Subsequently, a point-by-point plane fit was performed along these centerlines, and the normal vector of the semicircular canals was computed using the singular value decomposition method and calibrated to a standard spatial coordinate system whose transverse planes were the top of the common crus and the bottom of the eyeballs.Results: The nnDetection target recognition segmentation algorithm achieved Dice values of 0.9585 and 0.9663. The direction angles of the unit normal vectors for the left anterior, lateral, and posterior semicircular canal planes were [80.
Keywords: MRI, deep learning, semicircular canal, orientation 19°, 124.32°, 36.08°], [169.88°, 100.04°
Received: 05 Mar 2024; Accepted: 30 Aug 2024.
Copyright: © 2024 Zhou, Mao, Li, Li and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiaokai Yang, Third Affiliated Hospital, School of Medicine, Shanghai University, Shanghai, 200444, shanghai, China
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