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Breast cancer detection using combined curvelet based enhancement and a novel segmentation methods
B. Senthilkumar, G. Umamaheswari
Jazyk angličtina Země Česko
Typ dokumentu časopisecké články
NLK
Directory of Open Access Journals
od 2001
Free Medical Journals
od 1998
Medline Complete (EBSCOhost)
od 2007-06-01
ROAD: Directory of Open Access Scholarly Resources
od 2001
- MeSH
- lidé MeSH
- mamografie metody MeSH
- nádory prsu diagnostické zobrazování MeSH
- reprodukovatelnost výsledků MeSH
- ROC křivka MeSH
- teoretické modely * MeSH
- vylepšení rentgenového snímku * MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
AIM: This paper describes the digital implementation of a mathematical transform namely 2D Fast Discrete Curvelet Transform (FDCT) via UnequiSpaced Fast Fourier Transform (USFFT) in combination with the novel segmentation method for effective detection of breast cancer. METHODS: USFFT performs exact reconstructions with high image clarity. Radon, ridgelet and Cartesian filters are included in this method. Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) were calculated for the image and the resulting value showed that the proposed method performs well on mammogram image in reducing noise with good extraction of edges. This work includes a novel segmentation method, which combines Modified Local Range Modification (MLRM) and Laplacian of Gaussian (LoG) edge detection method to segment the textured features in the mammogram image. RESULTS: The result was analyzed using a Receiver Operating Characteristics (ROC) plot and the detection accuracy found was 99% which is good compared to existing methods.
Citace poskytuje Crossref.org
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