Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
De-noising hint Surfaces: A Physics-Based Approach
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
A Review of Nonlinear Diffusion Filtering
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Detection of clustered microcalcifications in small field digital mammography
Computer Methods and Programs in Biomedicine
| Hi-index | 0.00 |
Recent figures show that approximately 1 in 11 women in the western world will develop breast cancer during the course of their lives. Early detection greatly improves prognosis and considerable research has been undertaken to this end. Mammographic images are difficult to interpret even by radiologists and this makes their task error prone. One of the earliest non-palpable signs is the appearance of microcalcifications, typically 0.5 mm in diameter, representing small deposits of calcium salts in the breast. A novel approach to detecting microcalcifications in x-ray mammography has been explored. The method is based on the use of the physics-based image representation hint [1] and use of anisotropic diffusion to filter hint images. The diffusion process becomes a method of detecting both noise and microcalcifications in mammograms.