Prediction of Malaysian Talus Bone Morphology Using Artificial Intelligence

Rosdi, Daud and Nurazlina, Sulaeman and Mas Ayu, Hassan and Arman Shah, Abdullah (2022) Prediction of Malaysian Talus Bone Morphology Using Artificial Intelligence. In: Advanced Materials and Engineering Technologies. Advanced Structured Materials book series (STRUCTMAT), 162 . Springer Science and Business Media Deutschland GmbH, Springer Link Malaysia, pp. 29-37. ISBN 978-3-030-92963-3 (Printed); 978-3-030-92964-0(Online)

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Abstract

Book cover pp 29–37Cite as Part of the Abstract Talus fractures keep on presenting to a difficult and generally experienced gathering of injuries. This published report shows that not all the current bone implants are the ideal counterpart for the specific population. Along these lines, this investigation received a three-dimensional (3D) estimation way to deal with given exact information to the anatomical morphology of talus bone. Seventy-four Malaysian healthy subjects experienced computerized tomography (CT) arthrography. 3D computerized talar models were generated and three morphological boundaries predicted through Mimics and Solidworks software. Sagittal Talar radius (STRa), Throchlea Tali length (TTL), Talar Anterior width (TaAW) are the most part chosen. Information investigation was directed by determination of information test through Matlab programming. In this way, the information was obtained dependent on the artificial intelligence (AI) forecast of the talus bone morphometric. While, the AI strategy demonstrated a more noteworthy limit of forecast in regards to the low level of mistake and high correlative qualities since the average percentage errors of the predicted talus bone morphology parameters are around 10% which 11.3% for STRa, 12.95% for TaAW, and 9.45% for TTL. AI is an exceptionally exact prescient technique and can be utilized as helping instruments in developing bone implant specifically for Malaysian patient and for Asian patient in general.

Item Type: Book Chapter
Uncontrolled Keywords: Talus fracture; Bone morphometric; Artificial intelligent
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TS Manufactures
Faculty/Division: Institute of Postgraduate Studies
Faculty of Manufacturing and Mechatronic Engineering Technology
Faculty of Mechanical and Automotive Engineering Technology
Depositing User: Ms. Ratna Wilis Haryati Mustapa
Date Deposited: 15 Dec 2022 02:40
Last Modified: 15 Dec 2022 02:40
URI: http://umpir.ump.edu.my/id/eprint/35929
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