Classification of Malignant and Benign Tumours in Digital Mammograms
The Application of Computer Vision and Machine Learning Techniques
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Breast cancer is one of the most common kinds of cancer, as well as the leading cause of mortality among women. Mammography is currently the most effective imaging modality for the detection of breast cancer and the diagnosis of the anomalies which can identify cancerous cells. Retrospective studies show that, in current breast cancer screenings approximately 15 to 30 percent of breast cancer cases are missed by radiologists. With the advances in digital image processing techniques, it is envisaged that radiologists will have opportunities to decrease this margin of error and hence, improve th...
Breast cancer is one of the most common kinds of cancer, as well as the leading cause of mortality among women. Mammography is currently the most effective imaging modality for the detection of breast cancer and the diagnosis of the anomalies which can identify cancerous cells. Retrospective studies show that, in current breast cancer screenings approximately 15 to 30 percent of breast cancer cases are missed by radiologists. With the advances in digital image processing techniques, it is envisaged that radiologists will have opportunities to decrease this margin of error and hence, improve their diagnosis.
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