Abstract
Analyzing medical images is the most challenging task in medical image processing. Computer Aided Detection (CAD) tool is the aid for the radiologists in analyzing such images for the effective detection and diagnosis of the disease. Such a CAD tool consists of Preprocessing, Segmentation and detection processes. In this study we have improved the preprocessing by using the Selective Median Filter (SMF) for the noise removal and modified the Local Range Modification (LRM) as modified LRM (MLRM) for the contrast enhancement to detect the breast cancer. We have tested the performance of some preprocessing methods and compared with the proposed method (MLRM). These methods (SMF and MLRM) had been tested for over 30 mammogram images and found the accuracy of 97.9% which is better than the other existing methods.
Highlights
Breast cancer is the most dangerous disease for women over the age of 40
In this study we have improved the preprocessing by using the Selective Median Filter (SMF) for the noise removal and modified the Local Range Modification (LRM) as modified LRM (MLRM) for the contrast enhancement to detect the breast cancer
We have tested the performance of some preprocessing methods and compared with the proposed method (MLRM)
Summary
Breast cancer is the most dangerous disease for women over the age of 40. Early detection and treatment is the only possibility of control it. Breast cancer has been identified by taking sample tissue from the suspected breast area (biopsy). In this modern world, many CAD has been designed and it has been used by the radiologists as an aid for the effective detection of breast cancer (Yang et al, 2005; Cheng et al, 2006; Retico et al, 2006; Boccignone et al, 2000). CAD consists of preprocessing (noise removal and contrast enhancement), segmentation and detection. In this study we have discussed about the SMF for noise cancellation and the LRM, the MLRM for contrast enhancement
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have