Development of Scoliotic Spine Severity Detection using Deep Learning Algorithms-Reference-Cited by-同舟云学术

Development of Scoliotic Spine Severity Detection using Deep Learning Algorithms

Published:2022-01-26 Issue: Volume: Page:
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Container-title:2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC)
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Author:

Makhdoomi Nahid Ameer¹,Gunawan Teddy Surya¹,Idris Nur Hanani¹,Khalifa Othman Omran²,Karupiah Rajandra Kumar³,Bramantoro Arif⁴,Abdul Rahman Farah Diyana¹,Zakaria Zamzuri⁴

Affiliation:

1. Int. Islamic University Malaysia,ECE Department,Kuala Lumpur,Malaysia,53100

2. Int. Islamic University,ECE Department,Kuala Lumpur,Malaysia,53100

3. Traumatology & Rehabilitation IIUM Kuantan,Department of Orthopaedics,Pahang,Malaysia,25050

4. Universiti Teknologi Brunei,School of Computing and Informatics,Bandar Seri Begawan,Brunei

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9720724/9720434/09720906.pdf?arnumber=9720906

Reference15 articles.

1. Automatic segmentation of spinal ultrasound landmarks with U-net using multiple consecutive images for input

2. Evaluation of a computer-aided method for measuring the Cobb angle on chest X-rays

3. Cobb Angle Measurement of Spine from X-Ray Images Using Convolutional Neural Network

4. The Lenke Classification System of Operative Adolescent Idiopathic Scoliosis

5. Fully convolutional networks for semantic segmentation

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