Region-growing technique adapted to precise microcalcification characterization in mammography

Michel Darboux; Jean-Marc Dinten; Eric Nicolas

doi:10.1117/12.258280

14 November 1996 Region-growing technique adapted to precise microcalcification characterization in mammography

Michel Darboux, Jean-Marc Dinten, Eric Nicolas

Proceedings Volume 2847, Applications of Digital Image Processing XIX; (1996) https://doi.org/10.1117/12.258280
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

The early detection of breast cancer is essential for increasing the survival rate of the disease. Today, mammography is the only breast screening technique capable of detecting breast cancer at a very early stage. The presence of a breast tumor is indicated by some features on the mammogram. One sign of malignancy is the presence of clusters of fine, granular microcalcifications. We present here a three-step method for detecting and characterizing these microcalcifications. We begin with the detection of potential candidates. The aim of this first step is to detect all the pixels that could be a microcalcification. Then we focus on our specific region growing technique which provides an accurate extraction of the shape of the region corresponding to each detected growing technique which provides an accurate extraction of the shape of the region corresponding to each detected seed. This second step is essential because microcalcifications shape is a very important feature for the diagnosis. It is then possible to determine precise parameters to characterize these microcalcifications. This three-step method has been evaluated on a set of images form the mammographic image analysis society database.

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Michel Darboux, Jean-Marc Dinten, and Eric Nicolas "Region-growing technique adapted to precise microcalcification characterization in mammography", Proc. SPIE 2847, Applications of Digital Image Processing XIX, (14 November 1996); https://doi.org/10.1117/12.258280

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KEYWORDS

Tissues

Mammography

Breast

Breast cancer

Databases

Detection and tracking algorithms

Feature extraction

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