Correlative Feature Analysis for Multimodality Breast CAD
Abstract
The purpose of this research 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. During the second year of the project, we have expanded the multimodality database, which includes full-field digital mammograms, breast ultrasound images and breast MR images. We have further evaluated the performance of the proposed dual-stage segmentation method for the task of assessing the likelihood of malignancy of a mass lesion. We have developed a computerized correlative feature analysis framework to identify the correspondence between lesions imaged in different images, and evaluated its performance on two different mammographic view pairs, i.e. Cranio-Caudal versus Medio-Lateral and Cranio-Caudal versus Medio-Lateral-Oblique. Furthermore, we conducted a pilot study on computerized diagnosis of breast lesions with mammography and DCE-MRI.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2008
- Accession Number
- ADA508617
Entities
People
- Yading Yuan
Organizations
- University of Chicago