Paper
28 February 2013 Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statistics
Baek Hwan Cho, Chuho Chang, Jong-Ha Lee, Eun Young Ko, Yeong Kyeong Seong, Kyoung-Gu Woo
Author Affiliations +
Proceedings Volume 8670, Medical Imaging 2013: Computer-Aided Diagnosis; 86701Q (2013) https://doi.org/10.1117/12.2007458
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
The existence of microcalcifications (MCs) is an important marker of malignancy in breast cancer. In spite of the benefits in mass detection for dense breasts, ultrasonography is believed that it might not reliably detect MCs. For computer aided diagnosis systems, however, accurate detection of MCs has the possibility of improving the performance in both Breast Imaging-Reporting and Data System (BI-RADS) lexicon description for calcifications and malignancy classification. We propose a new efficient and effective method for MC detection using image enhancement and threshold adjacency statistics (TAS). The main idea of TAS is to threshold an image and to count the number of white pixels with a given number of adjacent white pixels. Our contribution is to adopt TAS features and apply image enhancement to facilitate MC detection in ultrasound images. We employed fuzzy logic, tophat filter, and texture filter to enhance images for MCs. Using a total of 591 images, the classification accuracy of the proposed method in MC detection showed 82.75%, which is comparable to that of Haralick texture features (81.38%). When combined, the performance was as high as 85.11%. In addition, our method also showed the ability in mass classification when combined with existing features. In conclusion, the proposed method exploiting image enhancement and TAS features has the potential to deal with MC detection in ultrasound images efficiently and extend to the real-time localization and visualization of MCs.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Baek Hwan Cho, Chuho Chang, Jong-Ha Lee, Eun Young Ko, Yeong Kyeong Seong, and Kyoung-Gu Woo "Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statistics", Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86701Q (28 February 2013); https://doi.org/10.1117/12.2007458
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Ultrasonography

Image enhancement

Breast

Platinum

Fuzzy logic

Breast cancer

Computer aided diagnosis and therapy

Back to Top