Paper Info
Title
Surrounding Region Dependence Method for Detection of Clustered Microcalcifications on Mammograms
Abstract
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 region. Four textural features are extracted from the SRDM. These features are used to class@ region of interests (ROls) into positive ROIs containing clustered microcalcifications and negative ROIs of normal breast tissues. The three-layer back propagation 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.
Year
DOI
Venue
1997
10.1109/ICIP.1997.632176
ICIP (3)
Keywords
Field
DocType
backpropagation,second order,feature extraction,data mining,image segmentation,breast cancer,receiver operator characteristic,statistical analysis,computer vision,image texture,region of interest,roc analysis,receiver operating characteristics,histograms,image classification,x ray detectors
Computer vision,Histogram,Receiver operating characteristic,Pattern recognition,Microcalcification,Computer science,Image texture,Feature extraction,Image segmentation,Artificial intelligence,Classifier (linguistics),Contextual image classification
Conference
Volume
ISBN
Citations 
3
0-8186-8183-7
0
PageRank 
References 
Authors
0.34
7
2
Name
Order
Citations
PageRank
Jong-Kook Kim152639.53
Hyun Wook Park249554.79