|
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.
| Limitations: |
 APPROVED FOR PUBLIC RELEASE |
| Description: |
Annual summary rept. 1 Sep 2007-31 Aug 2008 |
| Pages: |
37 |
| Report Date: |
Sep-2008 |
| Contract Number: |
W81XWH-06-1-0726 W81XWH0610726 |
| Report Number: |
A716805 |
|
|
|
|
|
Keywords relating to this report:
Email This Abstract
