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Cassification of breast tumor based on ultrasound images / Devendran Pillai Perumal

By:

Devendran Pillai Perumal

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2009Description: xii, 45 p. : ill. (some col.) ; 30 cm. + 1 computer discISBN:

THE0003987(Local)

Subject(s):

Breast -- Ultrasonic imaging

Dissertation note: Project paper (Bachelor of Chemical Engineering (Biotechnology)) -- Universiti Malaysia Pahang - 2009 Abstract: This research primarily focuses on the predictive technology of identifying the state of tumors in the breast tissues. In breast cancer diagnosis, patients are forced to undergo a series of biopsies just to identify and confirm on the state of tumor, as whether malignant or benign. In this research however, an algorithm will be developed using MATLAB Image Processing Toolbox to indentify the state of a tumor solely based on ultrasound images. Ultrasound images of breast tumors are imported into MATLAB and are passed through a set of filters to remove background noise. Next, the filtered images are run through a set of edge detection algorithms which identifies and defines the region of interest. The processed images are analyzed qualitatively and the following results are obtained; the analysis shows that malignant tumors have well defined boundaries while benign tumors have poorly defined boundaries. To test this theory, the algorithm is used to process another set of ultrasound images of unknown characteristics. The results were analyzed and classified into two groups; malignant and benign. The results are compared with the actual biopsy results from the IIUM Breast Cancer Research Institute, Kuantan and all the analyzed results matched the biopsy results. As a recommendation to improve this study, a quantitative analysis on the ultrasound images is carried out so that more accurate results can be obtained. If the development of this algorithm is proven to be a success, it would be used in every hospital throughout the country to diagnose patients with breast cancer.

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Holdings ( 2 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB GAMBANG	TP156.E8 D48 2009 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000060288
Final Year Report	UMPLIB GAMBANG	CD 5532 \| TP156.E8 D48 2009 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000060289

Project paper (Bachelor of Chemical Engineering (Biotechnology)) -- Universiti Malaysia Pahang - 2009

Bibliography : p. 39-40

This research primarily focuses on the predictive technology of identifying the state of tumors in the breast tissues. In breast cancer diagnosis, patients are forced to undergo a series of biopsies just to identify and confirm on the state of tumor, as whether malignant or benign. In this research however, an algorithm will be developed using MATLAB Image Processing Toolbox to indentify the state of a tumor solely based on ultrasound images. Ultrasound images of breast tumors are imported into MATLAB and are passed through a set of filters to remove background noise. Next, the filtered images are run through a set of edge detection algorithms which identifies and defines the region of interest. The processed images are analyzed qualitatively and the following results are obtained; the analysis shows that malignant tumors have well defined boundaries while benign tumors have poorly defined boundaries. To test this theory, the algorithm is used to process another set of ultrasound images of unknown characteristics. The results were analyzed and classified into two groups; malignant and benign. The results are compared with the actual biopsy results from the IIUM Breast Cancer Research Institute, Kuantan and all the analyzed results matched the biopsy results. As a recommendation to improve this study, a quantitative analysis on the ultrasound images is carried out so that more accurate results can be obtained. If the development of this algorithm is proven to be a success, it would be used in every hospital throughout the country to diagnose patients with breast cancer.