Improving Lesion Segmentation for Breast Cancer Detection

Islam, Md. Monjurul; Akash, Mobasshir Hossain; Islam, Shah Md. Injamamul

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dc.contributor.author	Islam, Md. Monjurul
dc.contributor.author	Akash, Mobasshir Hossain
dc.contributor.author	Islam, Shah Md. Injamamul
dc.date.accessioned	2022-04-25T06:29:54Z
dc.date.available	2022-04-25T06:29:54Z
dc.date.issued	2015-11-30
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dc.identifier.uri	http://hdl.handle.net/123456789/1400
dc.description	Supervised by Mr. Md. Taslim Reza Assistant Professor, Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT), Bangladesh.	en_US
dc.description.abstract	Breast cancer is the most common cause of death among patients and one of the main reasons is that the lesion is not identified properly. Ultrasound images are very difficult to segment due to presence of speckle noise and the boundaries of abnormal regions are too difficult to recognize due to similarity. For this reason, proper medical facility or treatment cannot be provided in time. The situation in Bangladesh is alarming as there is a huge female population in the rural areas who don’t have proper medical access to detect the early stage of breast cancer. We have implemented a Computer Aided Diagnosis (CAD) system that will detect the cancerous lesion in the BUS (breast ultrasound) images effectively. We implemented a region growing algorithm which can segment the object of interests (lesion). We place the seed on the ultrasound image (original image), check homogeneity and merge the homogeneous regions. After that we use horizontal cut based entropy filtering and at last by canny edge detection we subtract the object of interests (lesion) from the desired ultrasound image. We also implemented developed watershed algorithm and assimilated it with region growing algorithm	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh	en_US
dc.subject	Entropy, SRAD Filtering, Watershed Segmentation, Binary Thresholding, Canny Edge Detection.	en_US
dc.title	Improving Lesion Segmentation for Breast Cancer Detection	en_US
dc.type	Thesis	en_US