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Proceedings Paper

Investigating materials for breast nodules simulation by using segmentation and similarity analysis of digital images
Author(s): Paula N. Siqueira; Karem D. Marcomini; Maria A. Z. Sousa; Homero Schiabel
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Paper Abstract

The task of identifying the malignancy of nodular lesions on mammograms becomes quite complex due to overlapped structures or even to the granular fibrous tissue which can cause confusion in classifying masses shape, leading to unnecessary biopsies. Efforts to develop methods for automatic masses detection in CADe (Computer Aided Detection) schemes have been made with the aim of assisting radiologists and working as a second opinion. The validation of these methods may be accomplished for instance by using databases with clinical images or acquired through breast phantoms. With this aim, some types of materials were tested in order to produce radiographic phantom images which could characterize a good enough approach to the typical mammograms corresponding to actual breast nodules. Therefore different nodules patterns were physically produced and used on a previous developed breast phantom. Their characteristics were tested according to the digital images obtained from phantom exposures at a LORAD M-IV mammography unit. Two analysis were realized the first one by the segmentation of regions of interest containing the simulated nodules by an automated segmentation technique as well as by an experienced radiologist who has delineated the contour of each nodule by means of a graphic display digitizer. Both results were compared by using evaluation metrics. The second one used measure of quality Structural Similarity (SSIM) to generate quantitative data related to the texture produced by each material. Although all the tested materials proved to be suitable for the study, the PVC film yielded the best results.

Paper Details

Date Published: 18 March 2015
PDF: 8 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94123F (18 March 2015); doi: 10.1117/12.2082184
Show Author Affiliations
Paula N. Siqueira, Univ. de São Paulo (Brazil)
Karem D. Marcomini, Univ. de São Paulo (Brazil)
Maria A. Z. Sousa, Univ. de São Paulo (Brazil)
Homero Schiabel, Univ. de São Paulo (Brazil)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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