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A study on mammography computer aided diagnosis system using machine learning methods

机译:基于机器学习方法的乳腺X线计算机辅助诊断系统的研究

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Early diagnosis is an important aspect of successful treatment for breast cancer. Mammogram is the most reliable imaging technique available. It is a challenging task for radiologists to detect the abnormalities in the mammograms. Computing helps the radiologists in diagnosing the abnormalities in the mammogram. Computer Aided Diagnosis System involves computerized biomedical image analysis to classify the mammography into benign or malign. In a decade of research work number of algorithms had been proposed to classify the image that employ data mining techniques, image processing methods, machine learning methods and pattern recognition. In this paper such algorithms in previous research work is studied and their performance is discussed.
机译:早期诊断是成功治疗乳腺癌的重要方面。乳房X线照片是最可靠的成像技术。对于放射线医师来说,检测乳房X线照片中的异常是一项艰巨的任务。计算可以帮助放射科医生诊断乳房X线照片中的异常。计算机辅助诊断系统涉及计算机化的生物医学图像分析,以将乳房X线照相术分为良性或恶性。在十年的研究工作中,已经提出了多种算法来对图像进行分类,这些算法采用了数据挖掘技术,图像处理方法,机器学习方法和模式识别。在本文中,对此类算法进行了研究,并对其性能进行了讨论。

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