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ICIP
1997
IEEE

Surrounding Region Dependence Method for Detection of Clustered Microcalcifications on Mammograms

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Surrounding Region Dependence Method for Detection of Clustered Microcalcifications on Mammograms
Clustered microcalcifications on X-ray mammograms are an important feature in the detection of breast cancer. For the detection of the clustered microcalcifications on digitized mammograms, this paper proposes a texture analysis method called the surrounding region dependence method (SRDM), which is a statistical texture analysis based on the second-order histogram in two surrounding regions. Four textural features are extracted from the SRDM. These features are used to classify region of interests (ROIs) into positive ROIs containing clustered microcalcifications and negative ROIs of normal breast tissues. The three-layer backpropagation neural network is employed as a classifier with input data of four textural features. The classification performance of the proposed method is evaluated by using the round-robin method and the receiver operating-characteristics (ROC) analysis.
Jong-Kook Kim, Hyun Wook Park
Added 26 Oct 2009
Updated 26 Oct 2009
Type Conference
Year 1997
Where ICIP
Authors Jong-Kook Kim, Hyun Wook Park
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