Correlative Feature Analysis for Multimodality Breast CAD
Abstract
The purpose of this study is to develop correlative feature analysis methods for integrating image information from multi-modality breast images taking advantage of the information from different views and/or different modalities and thus improving the sensitivity and specificity of breast cancer diagnosis. Identifying the corresponding image pair of a lesion is an essential step for this purpose. During the first year we have collected and maintained a multi-modality breast image database which includes full field digital mammography (FFDM) sonography and MRI images. To differentiate corresponding FFDM image pairs from non-corresponding ones in which images were obtained from CC and ML view respectively we have developed computerized methods for lesion segmentation feature extraction and selection feature correlation analysis and image pair classification. The results have shown that our computerized feature correlative analysis has great potential in identifying the corresponding image pair of a lesion obtained from different views of the same modality.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2007
- Accession Number
- ADA475156
Entities
People
- Yading Yuan
Organizations
- University of Chicago