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Title |
An Automated Way to Detect Tumor in Liver |
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Author |
Meenu Sharma. Rafat Parveen |
| Citation |
Vol. 23 No. 10 pp. 209-213 |
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Abstract |
In recent years, the image processing mechanisms are used widely in several medical areas for improving earlier detection and treatment stages, in which the time factor is very important to discover the disease in the patient as possible as fast, especially in various cancer tumors such as the liver cancer. Liver cancer has been attracting the attention of medical and sciatic communities in the latest years because of its high prevalence allied with the difficult treatment. Statistics indicate that liver cancer, throughout world, is the one that attacks the greatest number of people. Over the time, study of MR images related to cancer detection in the liver or abdominal area has been difficult. Early detection of liver cancer is very important for successful treatment. There are few methods available to detect cancerous cells. In this paper, an automatic approach that integrates the intensity-based segmentation and k-means clustering approach for detection of cancer region in MRI scan images of liver. |
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Keywords |
liver tumor, magnetic resonance imaging, segmentation, feature extraction, image processing |
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