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Image Feature Extraction Method with SIFT to Diagnose Prostate Cancer

机译:图像特征提取方法筛选诊断前列腺癌

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Number of prostate cancer patients are increasing but diagnosing pathologists are not enough. Then supporting system to diagnose prostate cancer on biopsy image is needed by pathologists. However staining conditions of prostate biopsy images are uneven, so extracting their form by automatic method is difficult. Because of this problem, previous study aiming to diagnose each glandular needed to except imperfect extraction glandular. Then we propose new feature extraction method (Area Rates on Components and SIFT + BoK) aiming to improve accuracy on imperfect extracted glands. In our experiment, diagnosing accuracy is improved 6.3% ~ 13.3%.
机译:前列腺癌患者的数量正在增加,但诊断病理学家还不够。然后,病理学家需要支持系统来诊断前列腺癌的前列腺癌。然而,前列腺活组织检查图像的染色条件是不均匀的,因此通过自动方法提取它们的形式是困难的。由于这个问题,以前的研究旨在诊断每个腺体所需的腺体,除了不完美的提取腺体。然后,我们提出了新的特征提取方法(组件和Sift + Bok的区域速率),其旨在提高缺乏污垢提取的腺体的准确性。在我们的实验中,诊断精度提高了6.3%〜13.3%。

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