A computerized volumetric segmentation method applicable to multi-centre MRI data to support computer-aided breast tissue analysis, density assessment and lesion localization

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• 作者：Gokhan Ertas ; Simon J. Doran…
• 关键词：MRI ; Breast ; Segmentation ; Fuzzy c ; means ; Multi ; centre ; Multi ; instrument
• 刊名：Medical & Biological Engineering & Computing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：55
• 期：1
• 页码：57-68
• 全文大小：1710KB
• 刊物类别：Engineering
• 刊物主题：Human Physiology; Biomedical Engineering; Imaging / Radiology; Computer Applications;
• 出版者：Springer Berlin Heidelberg
• ISSN：1741-0444
• 卷排序：55

文摘

Density assessment and lesion localization in breast MRI require accurate segmentation of breast tissues. A fast, computerized algorithm for volumetric breast segmentation, suitable for multi-centre data, has been developed, employing 3D bias-corrected fuzzy c-means clustering and morphological operations. The full breast extent is determined on T1-weighted images without prior information concerning breast anatomy. Left and right breasts are identified separately using automatic detection of the midsternum. Statistical analysis of breast volumes from eighty-two women scanned in a UK multi-centre study of MRI screening shows that the segmentation algorithm performs well when compared with manually corrected segmentation, with high relative overlap (RO), high true-positive volume fraction (TPVF) and low false-positive volume fraction (FPVF), and has an overall performance of RO 0.94 ± 0.05, TPVF 0.97 ± 0.03 and FPVF 0.04 ± 0.06, respectively (training: 0.93 ± 0.05, 0.97 ± 0.03 and 0.04 ± 0.06; test: 0.94 ± 0.05, 0.98 ± 0.02 and 0.05 ± 0.07).