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- Author: Arjun Nelikanti
- Publisher: GRIN Publishing
- Year: 2015
- ISBN-10: 3656879540
- ISBN-13: 9783656879541
- Format: 14.8 x 21 x 0.3 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Colorectal Cancer MRI Image Segmentation Using Image Processing Techniques (e-book) (used book) | bookbook.eu
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Master's Thesis from the year 2014 in the subject Medicine - Biomedical Engineering, grade: 76, course: Image processing, language: English, abstract: Colorectal cancer is the third most commonly diagnosed cancer and the second leading cause of cancer death in men and women. Magnetic resonance imaging (MRI) established itself as the primary method for detection and staging in patients with colorectal cancer. MRI images of Colorectal cancer are used to detect the area and mean values of tumor area and distance from tumor area to other parts. The thesis describes algorithms for preprocessing, clustering and post processing of MRI images. Implemented algorithm for preprocessing using image enhancement techniques, clustering is done using adaptive k-means algorithm and post processing using image processing techniques in MATLAB.
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- Author: Arjun Nelikanti
- Publisher: GRIN Publishing
- Year: 2015
- ISBN-10: 3656879540
- ISBN-13: 9783656879541
- Format: 14.8 x 21 x 0.3 cm, minkšti viršeliai
- Language: English English
Master's Thesis from the year 2014 in the subject Medicine - Biomedical Engineering, grade: 76, course: Image processing, language: English, abstract: Colorectal cancer is the third most commonly diagnosed cancer and the second leading cause of cancer death in men and women. Magnetic resonance imaging (MRI) established itself as the primary method for detection and staging in patients with colorectal cancer. MRI images of Colorectal cancer are used to detect the area and mean values of tumor area and distance from tumor area to other parts. The thesis describes algorithms for preprocessing, clustering and post processing of MRI images. Implemented algorithm for preprocessing using image enhancement techniques, clustering is done using adaptive k-means algorithm and post processing using image processing techniques in MATLAB.
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