Breast lesions detection using FADHECAL and Multilevel Otsu Thresholding Segmentation in digital mammograms
Breast cancer is the most common cause of mortality among women. Early detection plays an important role to improve survival rates. Digital mammograms can be used to detect breast lesions within the breast tissue. However, digital mammograms have a limitation of low contrast images due to the low...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | en en en |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/4591/1/FH03-FSK-21-55109.pdf http://eprints.unisza.edu.my/4591/2/FH03-FSK-21-52802.png http://eprints.unisza.edu.my/4591/3/FH03-FSK-21-55109.pdf http://eprints.unisza.edu.my/4591/ |
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| Summary: | Breast cancer is the most common cause of mortality among women. Early detection plays an
important role to improve survival rates. Digital mammograms can be used to detect breast lesions
within the breast tissue. However, digital mammograms have a limitation of low contrast images due
to the low exposure factors used. As a result, the extraction of breast lesions using the region of interest
(ROI) tool will be difficult and, thus, lead to misclassification. This paper presents a novel technique to
detect breast lesions in digital mammograms, known as Fuzzy Anisotropic Diffusion Histogram Equalization Contrast Adaptive Limited (FADHECAL) incorporated with Multilevel Otsu Thresholding
Segmentation. FADHECAL will enhance the breast lesions by reducing the image noise while preserving
the details. Multilevel Otsu Thresholding Segmentation detects the breast lesions using the ROI tool at
different intensity levels. The performance of FADHECAL incorporated with Multilevel Otsu
Thresholding Segmentation has been tested on 115 digital mammograms from the Mammographic
Image Analysis Society (MIAS) database with the abnormal conditions. The efficiency of the proposed
technique is 94.8%, and the error rate is 5.2%. In conclusion, FADHECAL incorporated with the
Multilevel Otsu Thresholding Segmentation has provided sufficient detection of breast lesions with the
appropriate quality of the digital mammograms. |
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