Literature DB >> 24972858

Computer aided diagnosis of degenerative intervertebral disc diseases from lumbar MR images.

Ayse Betul Oktay1, Nur Banu Albayrak2, Yusuf Sinan Akgul3.   

Abstract

This paper presents a novel method for the automated diagnosis of the degenerative intervertebral disc disease in midsagittal MR images. The approach is based on combining distinct disc features under a machine learning framework. The discs in the lumbar MR images are first localized and segmented. Then, intensity, shape, context, and texture features of the discs are extracted with various techniques. A Support Vector Machine classifier is applied to classify the discs as normal or degenerated. The method is tested and validated on a clinical lumbar spine dataset containing 102 subjects and the results are comparable to the state of the art.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computer aided diagnosis; Degeneration; Degenerative disc disease; Desiccation; Herniation; Intervertebral disc; Lumbar; Machine learning

Mesh:

Year:  2014        PMID: 24972858     DOI: 10.1016/j.compmedimag.2014.04.006

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  8 in total

1.  Feasibility of Deep Learning Algorithms for Reporting in Routine Spine Magnetic Resonance Imaging.

Authors:  Kai-Uwe LewandrowskI; Narendran Muraleedharan; Steven Allen Eddy; Vikram Sobti; Brian D Reece; Jorge Felipe Ramírez León; Sandeep Shah
Journal:  Int J Spine Surg       Date:  2020-12

2.  Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants.

Authors:  Benjamin S Hopkins; Kenneth A Weber; Kartik Kesavabhotla; Monica Paliwal; Donald R Cantrell; Zachary A Smith
Journal:  World Neurosurg       Date:  2019-03-25       Impact factor: 2.104

Review 3.  Current development and prospects of deep learning in spine image analysis: a literature review.

Authors:  Biao Qu; Jianpeng Cao; Chen Qian; Jinyu Wu; Jianzhong Lin; Liansheng Wang; Lin Ou-Yang; Yongfa Chen; Liyue Yan; Qing Hong; Gaofeng Zheng; Xiaobo Qu
Journal:  Quant Imaging Med Surg       Date:  2022-06

Review 4.  Novel Magnetic Resonance Imaging Tools for the Diagnosis of Degenerative Disc Disease: A Narrative Review.

Authors:  Carlo A Mallio; Gianluca Vadalà; Fabrizio Russo; Caterina Bernetti; Luca Ambrosio; Bruno Beomonte Zobel; Carlo C Quattrocchi; Rocco Papalia; Vincenzo Denaro
Journal:  Diagnostics (Basel)       Date:  2022-02-06

Review 5.  Artificial Intelligence and Computer Aided Diagnosis in Chronic Low Back Pain: A Systematic Review.

Authors:  Federico D'Antoni; Fabrizio Russo; Luca Ambrosio; Luca Bacco; Luca Vollero; Gianluca Vadalà; Mario Merone; Rocco Papalia; Vincenzo Denaro
Journal:  Int J Environ Res Public Health       Date:  2022-05-14       Impact factor: 4.614

6.  Diagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methods.

Authors:  Yüksel Maraş; Gül Tokdemir; Kemal Üreten; Ebru Atalar; Semra Duran; Hakan Maraş
Journal:  Jt Dis Relat Surg       Date:  2022-03-28

7.  Artificial intelligence in orthopaedics: A scoping review.

Authors:  Simon J Federer; Gareth G Jones
Journal:  PLoS One       Date:  2021-11-23       Impact factor: 3.240

Review 8.  Machine Learning in Orthopedics: A Literature Review.

Authors:  Federico Cabitza; Angela Locoro; Giuseppe Banfi
Journal:  Front Bioeng Biotechnol       Date:  2018-06-27
  8 in total

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