Literature DB >> 16554233

Projection profile analysis for identifying different views of chest radiographs.

E-Fong Kao1, Chungnan Lee, Twei-Shiun Jaw, Jui-Sheng Hsu, Gin-Chung Liu.   

Abstract

RATIONALE AND
OBJECTIVES: For computerized analysis of chest images in the clinical environment, identification of frontal (posteroanterior/anteroposterior) and lateral chest radiographs is an important preprocessing step. In this study, we developed a method to distinguish frontal from lateral views of the chest radiographs based on an analysis of the projection profile.
MATERIALS AND METHODS: Projection profile is obtained by projecting a chest image on to the mediolateral axis. Two indices, body symmetry index and background percentage index, are computed from the projection profile. The combination of body symmetry index and background percentage index is used to determine the view of chest radiographs. The method is evaluated on a sample of 2000 frontal and 1000 lateral chest images.
RESULTS: The values of body symmetry index are found to be 1.18 +/- 0.23 and 3.07 +/- 1.42 for frontal and lateral chest images, respectively. The values of background percentage index are found to be 0.03 +/- 0.05 and 0.33 +/- 0.09 for frontal and lateral chest images, respectively. The discrimination is evaluated by linear discriminant analysis and receiver operating characteristic analysis. Area Az under the receiver operating characteristic curve with the combination of the two indices is 0.993.
CONCLUSION: The method can be used as a preprocessing step for further analysis in chest radiographs.

Mesh:

Year:  2006        PMID: 16554233     DOI: 10.1016/j.acra.2006.01.009

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  3 in total

1.  Angular relational signature-based chest radiograph image view classification.

Authors:  K C Santosh; Laurent Wendling
Journal:  Med Biol Eng Comput       Date:  2018-01-22       Impact factor: 2.602

2.  Deep Transfer Learning for COVID-19 Prediction: Case Study for Limited Data Problems.

Authors:  Saleh Albahli; Waleed Albattah
Journal:  Curr Med Imaging       Date:  2021

3.  Detection of coronavirus disease from X-ray images using deep learning and transfer learning algorithms.

Authors:  Saleh Albahli; Waleed Albattah
Journal:  J Xray Sci Technol       Date:  2020       Impact factor: 1.535

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.