Multi-modal Complete Breast Segmentation

• Type: Article in International Conference Proceedings Book
• Date: 2017

Authors

Zolfagharnasab, H (Author) Other; Monteiro, JP (Author) Other; João Teixeira (Author) FEUP; Borlinhas, F (Author) Other; Oliveira, HP (Author) FCUP

Conference proceedings International

Title: PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2017)

Pages: 519-527

8th Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA)

Univ Algarve, Faro, PORTUGAL, JUN 20-23, 2017

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Other information

Authenticus ID: P-00M-WZ8

DOI: 10.1007/978-3-319-58838-4_57

Abstract (EN): Automatic segmentation of breast is an important step in the context of providing a planning tool for breast cancer conservative treatment, being important to segment completely the breast region in an objective way; however, current methodologies need user interaction or detect breast contour partially. In this paper, we propose a methodology to detect the complete breast contour, including the pectoral muscle, using multi-modality data. Exterior contour is obtained from 3D reconstructed data acquired from low-cost RGB-D sensors, and the interior contour (pectoral muscle) is obtained from Magnetic Resonance Imaging (MRI) data. Quantitative evaluation indicates that the proposed methodology performs an acceptable detection of breast contour, which is also confirmed by visual evaluation.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9