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Breast tumor segmentation in high resolution x-ray phase contrast analyzer based computed tomography

Authors :
Brun, E
Grandl, S
Sztrokay-Gaul, A
Barbone, G
Mittone, A
Gasilov, S
Bravin, A
Coan, P
Brun E
Grandl S
Sztrokay-Gaul A
Barbone G
Mittone A
Gasilov S
Bravin A
Coan P
Brun, E
Grandl, S
Sztrokay-Gaul, A
Barbone, G
Mittone, A
Gasilov, S
Bravin, A
Coan, P
Brun E
Grandl S
Sztrokay-Gaul A
Barbone G
Mittone A
Gasilov S
Bravin A
Coan P
Publication Year :
2014

Abstract

Purpose: Phase contrast computed tomography has emerged as an imaging method, which is able to outperform present day clinical mammography in breast tumor visualization while maintaining an equivalent average dose. To this day, no segmentation technique takes into account the specificity of the phase contrast signal. In this study, the authors propose a new mathematical framework for human-guided breast tumor segmentation. This method has been applied to high-resolution images of excised human organs, each of several gigabytes. Methods: The authors present a segmentation procedure based on the viscous watershed transform and demonstrate the efficacy of this method on analyzer based phase contrast images. The segmentation of tumors inside two full human breasts is then shown as an example of this procedures possible applications. Results: A correct and precise identification of the tumor boundaries was obtained and confirmed by manual contouring performed independently by four experienced radiologists. Conclusions: The authors demonstrate that applying the watershed viscous transform allows them to perform the segmentation of tumors in high-resolution x-ray analyzer based phase contrast breast computed tomography images. Combining the additional information provided by the segmentation procedure with the already high definition of morphological details and tissue boundaries offered by phase contrast imaging techniques, will represent a valuable multistep procedure to be used in future medical diagnostic applications.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1308941283
Document Type :
Electronic Resource