Journal
CURRENT MEDICAL IMAGING
Volume 17, Issue 9, Pages 1078-1084Publisher
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1573405617666210127101101
Keywords
Breast cancer screening; breast carcinoma; breast imaging; contrast enhancement; microcalcifications; image pro-cessing
Ask authors/readers for more resources
The study reviewed and compared various image enhancement techniques in digital mammograms for breast cancer detection. Among the four types of techniques, the filter-based method had the highest PSNR values. Frequency-based technique showed superior performance in MSE, AMBE, Entropy, and CII values.
Background: Digital mammograms with appropriate image enhancement techniques will improve breast cancer detection, and thus increase the survival rates. The objectives of this study were to systematically review and compare various image enhancement techniques in digital mammograms for breast cancer detection. Methods: A literature search was conducted with the use of three online databases namely, Web of Science, Scopus, and ScienceDirect. Developed keywords strategy was used to include only the relevant articles. A Population Intervention Comparison Outcomes (PICO) strategy was used to develop the inclusion and exclusion criteria. Image quality was analyzed quantitatively based on peak signal-noise-ratio (PSNR), Mean Squared Error (MSE), Absolute Mean Brightness Error (AMBE), Entropy, and Contrast Improvement Index (CII) values. Results: Nine studies with four types of image enhancement techniques were included in this study. Two studies used histogram-based, three studies used frequency-based, one study used fuzzy-based and three studies used filter-based techniques. All studies reported PSNR values whilst only four studies reported MSE, AMBE, Entropy, and CII values. Filter-based was the highest PSNR values of 78.93, among other types. For MSE, AMBE, Entropy, and CII values, the highest were frequency-based (7.79), fuzzy-based (93.76), filter-based (7.92), and frequency-based (6.54) respectively. Conclusion: In summary, image quality for each image enhancement technique is varied, especially for breast cancer detection. In this study, the frequency-based of Fast Discrete Curvelet Transform (FDCT) via the UnequiSpaced Fast Fourier Transform (USFFT) shows the most superior among other image enhancement techniques.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available