Literature DB >> 19162696

A preliminary study on discrimination of osteoporotic fractured group from nonfractured group using support vector machine.

Sooyeul Lee1, Jeong Won Lee, Ji-Wook Jeong, Done-Sik Yoo, Seunghwan Kim.   

Abstract

Osteoporosis is characterized by an abnormal loss of bone mineral content, which leads to a tendency to non-traumatic bone fractures or to structural deformations of bone. Thus, bone density has been considered as a most reliable parameter to assess osteoporotic fracture risk. In past decades, by the way, bone texture measures have been studied to estimate other aspect of bone quality. Some studies have been performed on CT or MR images to assess bone quality using trabecular structure analysis. Other studies have been performed on plain x-ray images or ultrasound images to assess trabecular structure. However, most of the studies are focused on individual parameters to distinguish between osteoporotic fractured group and nonfractured group. In this preliminary study, we combine various texture parameters with bone density parameters using a support vector machine and point out the most promising combination of parameters to distinguish between osteoporotic fractured group and nonfractured group.

Entities:  

Mesh:

Year:  2008        PMID: 19162696     DOI: 10.1109/IEMBS.2008.4649193

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  5 in total

1.  Early diagnosis of osteoporosis using radiogrammetry and texture analysis from hand and wrist radiographs in Indian population.

Authors:  A S Areeckal; N Jayasheelan; J Kamath; S Zawadynski; M Kocher; S David S
Journal:  Osteoporos Int       Date:  2017-12-03       Impact factor: 4.507

2.  Relationship between bone mineral density and trabecular bone pattern in postmenopausal osteoporotic Brazilian women.

Authors:  Matheus Lima Oliveira; Esio Fortaleza Nascimento Chaves Pedrosa; Adriana Dibo Cruz; Francsico Haiter-Neto; Francisco Jose Albuquerque Paula; Plauto Christopher Aranha Watanabe
Journal:  Clin Oral Investig       Date:  2012-12-14       Impact factor: 3.573

3.  Classification of women with and without hip fracture based on quantitative computed tomography and finite element analysis.

Authors:  K K Nishiyama; M Ito; A Harada; S K Boyd
Journal:  Osteoporos Int       Date:  2013-08-16       Impact factor: 4.507

Review 4.  Artificial intelligence on the identification of risk groups for osteoporosis, a general review.

Authors:  Agnaldo S Cruz; Hertz C Lins; Ricardo V A Medeiros; José M F Filho; Sandro G da Silva
Journal:  Biomed Eng Online       Date:  2018-01-29       Impact factor: 2.819

5.  Comparison of the Classification Results Accuracy for CT Soft Tissue and Bone Reconstructions in Detecting the Porosity of a Spongy Tissue.

Authors:  Róża Dzierżak; Zbigniew Omiotek; Ewaryst Tkacz; Sebastian Uhlig
Journal:  J Clin Med       Date:  2022-08-03       Impact factor: 4.964

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.