Paper Info
Title
Computer-aided diagnosis of mammographic masses using geometric verification-based image retrieval.
Abstract
Computer-Aided Diagnosis of masses in mammograms is an important indicator of breast cancer. The use of retrieval systems in breast examination is increasing gradually. In this respect, the method of exploiting the vocabulary tree framework and the inverted file in the mammographic masse retrieval have been proved high accuracy and excellent scalability. However it just considered the features in each image as a visual word and had ignored the spatial configurations of features. It greatly affect the retrieval performance. To overcome this drawback, we introduce the geometric verification method to retrieval in mammographic masses. First of all, we obtain corresponding match features based on the vocabulary tree framework and the inverted file. After that, we grasps the main point of local similarity characteristic of deformations in the local regions by constructing the circle regions of corresponding pairs. Meanwhile we segment the circle to express the geometric relationship of local matches in the area and generate the spatial encoding strictly. Finally we judge whether the matched features are correct or not, based on verifying the all spatial encoding are whether satisfied the geometric consistency. Experiments show the promising results of our approach.
Year
DOI
Venue
2017
10.1117/12.2255799
Proceedings of SPIE
Keywords
Field
DocType
Computer-Aided Diagnosis (CAD),Breast masses,image retrieval,geometric verification,mammography
Inverted index,Computer vision,Mammography,Computer science,Computer-aided diagnosis,Image retrieval,Artificial intelligence,Computer programming,Scalability,Encoding (memory),Visual Word
Conference
Volume
ISSN
Citations 
10134
0277-786X
0
PageRank 
References 
Authors
0.34
1
8
Name
Order
Citations
PageRank
Qingliang Li101.35
WeiLi Shi215.10
Huamin Yang31917.29
Huimao Zhang401.01
Guoxin Li553.16
Tao Chen64921.43
Kensaku Mori71125160.28
Zhengang Jiang8226.42