{"id":1332,"date":"2021-10-14T11:03:12","date_gmt":"2021-10-14T03:03:12","guid":{"rendered":"https:\/\/www.bebi.ntu.edu.tw\/?p=1332"},"modified":"2022-02-14T11:06:52","modified_gmt":"2022-02-14T03:06:52","slug":"%e7%94%9f%e9%86%ab%e9%9b%bb%e8%b3%87%e6%89%80%e6%95%99%e5%b8%ab%e7%a0%94%e7%a9%b6%e4%ba%ae%e9%bb%9e-110%e5%b9%b410%e6%9c%88%e4%bb%bd%e3%80%8c%e5%bc%b5%e7%91%9e%e5%b3%b0%e6%95%99%e6%8e%88%e3%80%8d","status":"publish","type":"post","link":"https:\/\/www.bebi.ntu.edu.tw\/?p=1332","title":{"rendered":"\u751f\u91ab\u96fb\u8cc7\u6240\u6559\u5e2b\u7814\u7a76\u4eae\u9ede-110\u5e7410\u6708\u4efd\u300c\u5f35\u745e\u5cf0\u6559\u6388\u300d"},"content":{"rendered":"

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In response to the Ministry of Science and Technology’s promotion about AI innovation research projects and focusing on AI core technologies.Professor “Ruey-Feng, Chang ” leads the research and development team (R&D team) and has dedicated to research the application of deep learning technology in the field of medical imaging.His team develops the automated computer-aided diagnosis and diagnosis system for medical imaging. The highlights of the team\u2019s academic research in recent years have focused on:<\/p>\n

ABUS Cancer Computer-aided Detection and Diagnosis System<\/u>The “ABUS Cancer Computer-aided Detection and Diagnosis System” is a breast cancer detection and diagnosis system designed with the artificial intelligence technology. is developed to locate the breast tumor in automatic whole breast ultrasound image (ABUS). Through the one-take and the one-stage detection architecture, our CADe can completely review an ABUS image within 1 second. Our system has properties of high detection rate, high diagnosis rate, low false positive (FP), robustness (tumor size < 1 cm), and high diagnosis accuracy. In detection, it has only 2 FPs in 95% sensitivity, and significantly reduces the detection time, which indicates the system is of great worth in clinical breast examination. Moreover, in breast cancer diagnosis, the accuracy rate of our system is up to 89.2%, and has high value in clinic.\"\"<\/a><\/p>\n

\u300c\u591a\u75be\u75c5\u80f8\u90e8X\u5149\u96fb\u8166\u8f14\u52a9\u8a3a\u65b7\u7cfb\u7d71\u300d<\/p>\n

\u80f8\u90e8X\u5149\u96fb\u8166\u8f14\u52a9\u8a3a\u65b7\u7cfb\u7d71\uff0c\u80fd\u8a3a\u65b7\u51fa14\u7a2e\u5e38\u898b\u7684\u80f8\u8154\u75be\u75c5\uff0c\u5305\u62ec\u80ba\u4e0d\u5f35\u3001\u5be6\u8b8a\u3001\u6d78\u6f64\u3001\u6c23\u80f8\u3001\u6c34\u816b\u3001\u6c23\u816b\u3001\u7e96\u7dad\u5316\u3001\u7a4d\u6db2\u3001\u80ba\u708e\u3001\u80f8\u819c\u589e\u539a\u3001\u5fc3\u81df\u80a5\u5927\u3001\u7d50\u7bc0\u3001\u816b\u584a\u548c\u759d\u6c23\u3002\u9ad8\u6548\u5716\u50cf\u8868\u5fb5\u63d0\u53d6\u5668\u8207\u589e\u5f37\u7684\u75be\u75c5\u95dc\u806f\u6027\u8cc7\u8a0a\u5e6b\u52a9X\u5149\u5f71\u50cf\u5206\u985e\u4e0d\u540c\u80f8\u8154\u75be\u75c5\u3002\u672c\u7cfb\u7d71\u6bd4\u6700\u5148\u9032\u7684 (SOTA) \u6280\u8853\u64c1\u6709\u66f4\u597d\u7684\u6548\u80fd(\u5e73\u5747AUC \u53ef\u9054 0.8266)\uff0c\u6e1b\u5c11\u4e86\u95b1\u7247\u8005\u9593\u8b8a\u7570\uff0c\u5ba2\u89c0\u5730\u63d0\u4f9b\u8a3a\u65b7\u7d50\u679c\u3002<\/p>\n

Multi-disease Thorax X-ray CADx system<\/u><\/p>\n

The chest X-ray is one of the most common imaging examinations in clinical diagnosis on the lung. Our thorax X-ray CADx system is useful for diagnosing different thorax diseases, which has excellent diagnostic accuracy and reduces viewer variances.Four advantages of the Thorax X-ray CADx system:<\/p>\n

    \n
  1. 14 thorax diseases diagnosis in one CADx system<\/li>\n<\/ol>\n

    Atelectasis, Consolidation, Infiltration, Pneumothorax, Edema, Emphysema, Fibrosis, Effusion, Pneumonia, Pleural thickening, Cardiomegaly, Nodule, Mass, and Hernia included.<\/p>\n

      \n
    1. Efficient image representation feature extractor<\/li>\n<\/ol>\n

      Extract representative image information.<\/p>\n

        \n
      1. Enhance the correlation between different thorax diseases<\/li>\n<\/ol>\n

        Fibrosis \u2192 Atelectasis, Pleural Effusion \u2192 Atelectasis.<\/p>\n

          \n
        1. Accurate diagnostic performance<\/li>\n<\/ol>\n

          Better diagnostic performance than SOTA (mean AUC = 0.8266).\"\"<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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