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- W4313824422 abstract "For diagnosing breast abnormalities, mammography and ultrasound are widely used due to the ease of use and low cost. Mammography uses ionizing radiations which are unsuitable for pregnant women; hence, ultrasound is preferred for examination. Ultrasound images are marred by speckle noise, resulting in masking of important diagnostic information, which makes it challenging for radiologists to differentiate between breast abnormalities. For breast tumor characterization, most of the studies have used statistical, signal processing or transform domain-based methods for texture quantification. However, use of local binary pattern (LBP) texture features in combination with morphological features has not been reported. The present work proposes an efficient CAD system for the characterization of breast ultrasound images based on LBP texture features and morphological features. The results illustrate that the CAD system based on the ANFC-LH algorithm yields optimal performance for breast tumor characterization." @default.
- W4313824422 created "2023-01-09" @default.
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- W4313824422 date "2023-01-01" @default.
- W4313824422 modified "2023-10-01" @default.
- W4313824422 title "LBP-Based CAD System Designs for Breast Tumor Characterization" @default.
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- W4313824422 doi "https://doi.org/10.1007/978-3-031-15816-2_13" @default.
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