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A Screening CAD Tool for the Detection of Microcalcification Clusters in Mammograms.


ABSTRACT: Breast cancer is the most common cancer diagnosed in women worldwide. Up to 50% of non-palpable breast cancers are detected solely through microcalcification clusters in mammograms. This article presents a novel and completely automated algorithm for the detection of microcalcification clusters in a mammogram. A multiscale 2D non-linear energy operator is proposed for enhancing the contrast between the microcalcifications and the background. Several texture, shape, intensity, and histogram of oriented gradients (HOG)-based features are used to distinguish microcalcifications from other brighter mammogram regions. A new majority class data reduction technique based on data distribution is proposed to counter data imbalance problem. The algorithm is able to achieve 100% sensitivity with 2.59, 1.78, and 0.68 average false positives per image on Digital Database for Screening Mammography (scanned film), INbreast (direct radiography) database, and PGIMER-IITKGP mammogram (direct radiography) database, respectively. Thus, it might be used as a second reader as well as a screening tool to reduce the burden on radiologists.

SUBMITTER: Karale VA 

PROVIDER: S-EPMC6737166 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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A Screening CAD Tool for the Detection of Microcalcification Clusters in Mammograms.

Karale Vikrant A VA   Ebenezer Joshua P JP   Chakraborty Jayasree J   Singh Tulika T   Sadhu Anup A   Khandelwal Niranjan N   Mukhopadhyay Sudipta S  

Journal of digital imaging 20191001 5


Breast cancer is the most common cancer diagnosed in women worldwide. Up to 50% of non-palpable breast cancers are detected solely through microcalcification clusters in mammograms. This article presents a novel and completely automated algorithm for the detection of microcalcification clusters in a mammogram. A multiscale 2D non-linear energy operator is proposed for enhancing the contrast between the microcalcifications and the background. Several texture, shape, intensity, and histogram of or  ...[more]

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