Mammographic Images Enhancement and Denoising for Breast Cancer Detection Using Dyadic Wavelet Processing
- 28 May 2008
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Instrumentation and Measurement
- Vol. 57 (7), 1422-1430
- https://doi.org/10.1109/tim.2007.915470
Abstract
Mammography is the most effective method for the early detection of breast diseases. However, the typical diagnostic signs such as microcalcifications and masses are difficult to detect because mammograms are low-contrast and noisy images. In this paper, a novel algorithm for image denoising and enhancement based on dyadic wavelet processing is proposed. The denoising phase is based on a local iterative noise variance estimation. Moreover, in the case of microcalcifications, we propose an adaptive tuning of enhancement degree at different wavelet scales, whereas in the case of mass detection, we developed a new segmentation method combining dyadic wavelet information with mathematical morphology. The innovative approach consists of using the same algorithmic core for processing images to detect both microcalcifications and masses. The proposed algorithm has been tested on a large number of clinical images, comparing the results with those obtained by several other algorithms proposed in the literature through both analytical indexes and the opinions of radiologists. Through preliminary tests, the method seems to meaningfully improve the diagnosis in the early breast cancer detection with respect to other approaches.Keywords
This publication has 12 references indexed in Scilit:
- Detection of masses in mammography through redundant expansions of scalePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Noise estimation in digital images using fuzzy processingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Computerized radiographic mass detection. II. Decision support by featured database visualization and modular neural networksIEEE Transactions on Medical Imaging, 2001
- De-noising by soft-thresholdingIEEE Transactions on Information Theory, 1995
- The discrete wavelet transform: wedding the a trous and Mallat algorithmsIEEE Transactions on Signal Processing, 1992
- Characterization of signals from multiscale edgesIeee Transactions On Pattern Analysis and Machine Intelligence, 1992
- Entropy-based algorithms for best basis selectionIEEE Transactions on Information Theory, 1992
- A review of false negative mammography in a symptomatic populationClinical Radiology, 1991
- The Role of the Reference Radiologist; Estimates of Inter-Observer Agreement and Potential Delay in Cancer Detection in the National Breast Screening StudyInvestigative Radiology, 1990
- A theory for multiresolution signal decomposition: the wavelet representationIeee Transactions On Pattern Analysis and Machine Intelligence, 1989