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Using logistic regression to distinguish between fatty and fibroid masses in medical imaging (ultrasound image)
Author
Source
ZANCO Journal of Pure and Applied Sciences
Issue
Vol. 28, Issue 5 (31 Oct. 2016), pp.193-201, 9 p.
Publisher
Salahaddin University-Erbil Department of Scientific Publications
Publication Date
2016-10-31
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Abstract EN
Medical image analysis has great significance in the field of medicine, especially in non-invasive and clinical studies.
Medical imaging techniques and it analysis tools enable the physicians and Radiologists to reach at a specific diagnosis .In this study has been studying the link between (statistical model ,Computer vision and medical images) using the application binary logistic model to analyze medical imaging (Ultrasound image for breast), for distinguishing between shape of mass (Fatty & Fibroid) through selecting regions of interest (ROI) of the mass, and by extracting statistical and geometric measurements ( Mean, Standard Deviation, Circle, Solidity,…..), best logistic model was able to be estimated which is composed of significance parameters (Integrated Density, Median, Skew, Kurt), Then, It was reached a good percentage of the classification and distinction between (Fibroid) and (Fatty) masses (85.7% vs.
82.9%) with the total percentage of classification equal to 84.4
American Psychological Association (APA)
Ahmad, Rizgar M.. 2016. Using logistic regression to distinguish between fatty and fibroid masses in medical imaging (ultrasound image). ZANCO Journal of Pure and Applied Sciences،Vol. 28, no. 5, pp.193-201.
https://search.emarefa.net/detail/BIM-756719
Modern Language Association (MLA)
Ahmad, Rizgar M.. Using logistic regression to distinguish between fatty and fibroid masses in medical imaging (ultrasound image). ZANCO Journal of Pure and Applied Sciences Vol. 28, no. 5 (2016), pp.193-201.
https://search.emarefa.net/detail/BIM-756719
American Medical Association (AMA)
Ahmad, Rizgar M.. Using logistic regression to distinguish between fatty and fibroid masses in medical imaging (ultrasound image). ZANCO Journal of Pure and Applied Sciences. 2016. Vol. 28, no. 5, pp.193-201.
https://search.emarefa.net/detail/BIM-756719
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 200-201
Record ID
BIM-756719