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Design and introduce of diagnostic software for breast lesions in MR mammography with contrast
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M Sadeghi Moghadam   , M H Bahrini Toosi , M Sajjadi , A.R Mahmudabadi , M Talasaz |
| Gonabad University of Medical Sciences, Gonabad, Iran , sadeghimm881@gmail.com |
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Abstract: (8530 Views) |
| Introduction: Breast cancer is the most prevalent malignancy of women in the world, including Iran. In order to diagnose the breast lesions in early stage, various medical imaging modalities are rapidly developing. The purpose of this study was to design and introduce a diagnostic software for breast lesions in breast MR mammography. Materials & Methods: This research was a software designing study that MR mammography images from 31 patients with 54 lesions were analyzed with the software designer. The designed software was in Mathlab and could evaluate morphologic and physiologic traits of lesions. Based on the evidences from this analysis, radiologist could make decision about the malignity or benignity of the lesions. The results of all lesion diagnostics were analyzed and compared in the pathologist’s report. Data were analyzed using SPSS/16. Findings: Designed software enables the present MR mammography images in colure format and analyzes them pixel by pixel. This software in addition evaluates the shape, the margin and the internal texture of mass lesions and presents their physiologic and morphologic data and assists the diagnostics of lesion. Final results of diagnostic software analysis showed 94.1% sensitivity and 85% specificity. Conclusion: Contemporary assessments of morphologic and physiologic traits of lesions by a computer aided diagnostic software can improve the radiologist’s precision and decrease reading time of bulk images of every MR mammography. Using this software to increase the accuracy of the breast lesions detection is suggested. |
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| Keywords: MR Mammography, Contrast media, Benign, Malignancy, Software |
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Full-Text [PDF 222 kb]
(2459 Downloads)
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Type of Study: Research |
Subject:
health management
Received: 2016/02/2 | Accepted: 2016/06/21 | Published: 2016/06/21
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