Title :
Detection and retrieval of cysts in joint ultrasound B-mode and elasticity breast images
Author :
Zhang, Jingdan ; Zhou, Shaohua Kevin ; Brunke, Shelby ; Lowery, Carol ; Comaniciu, Dorin
Author_Institution :
Robust Anal. & Content Retrieval Program, Siemens Corp. Res., Princeton, NJ, USA
Abstract :
Distinguishing cysts from other tumors is a routine clinical practice for diagnosing breast cancer. It has shown that more accurate diagnosis can be achieved by combining elasticity images with traditional B-mode ultrasound images. In this paper, we propose a fully automatic system to detect cysts jointly in both B-mode and elasticity images. It is based on database-guided techniques that learn the knowledge of cyst appearance automatically from B-mode and elasticity images in a database. Further, for a detected cyst in a query image, the cysts with similar image appearance in the database are retrieved to improve diagnostic accuracy and confidence. In the experiment, we show that our system achieves high sensitivity and specificity in cyst diagnosis.
Keywords :
biological organs; biomechanics; biomedical ultrasonics; elasticity; gynaecology; image retrieval; medical image processing; tumours; breast cancer; cyst appearance; cyst detection; cyst retrieval; fully automatic system; joint ultrasound B-mode imaging; joint utlrasound elasticity imaging; Breast cancer; Breast neoplasms; Content based retrieval; Costs; Elasticity; Image databases; Image retrieval; Information retrieval; Robustness; Ultrasonic imaging; breast cyst detection and retrieval; elasticity imaging; ultrasound (US) imaging;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2010.5490387