{"id":1444,"date":"2023-05-20T19:18:49","date_gmt":"2023-05-20T11:18:49","guid":{"rendered":"https:\/\/sanlangcode.com\/?p=1444"},"modified":"2023-05-20T19:18:49","modified_gmt":"2023-05-20T11:18:49","slug":"%e5%85%a5%e9%97%a8-%e6%b5%85%e8%b0%88%e5%8c%bb%e5%ad%a6%e5%9b%be%e5%83%8f%e5%a4%84%e7%90%86%e3%80%90%e8%bd%ac%e3%80%91","status":"publish","type":"post","link":"https:\/\/sanlangcode.com\/index.php\/2023\/05\/20\/%e5%85%a5%e9%97%a8-%e6%b5%85%e8%b0%88%e5%8c%bb%e5%ad%a6%e5%9b%be%e5%83%8f%e5%a4%84%e7%90%86%e3%80%90%e8%bd%ac%e3%80%91\/","title":{"rendered":"\u5165\u95e8-\u6d45\u8c08\u533b\u5b66\u56fe\u50cf\u5904\u7406\u3010\u8f6c\u3011"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">\u4e00\u3001\u533b\u5b66\u56fe\u50cf\u5904\u7406\u7684\u610f\u4e49<\/h2>\n\n\n\n<p>\u533b\u5b66\u56fe\u50cf\u662f\u53cd\u6620\u4eba\u4f53\u5185\u90e8\u7ed3\u6784\u7684\u56fe\u50cf\uff0c\u662f\u73b0\u4ee3\u533b\u7597\u8bca\u65ad\u7684\u4e3b\u8981\u4f9d\u636e\u4e4b\u4e00\u3002\u76ee\u524d\uff0c\u533b\u5b66\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u4e3b\u8981\u96c6\u4e2d\u5728\u56fe\u50cf\u68c0\u6d4b\u3001\u56fe\u50cf\u5206\u5272\u3001\u56fe\u50cf\u914d\u51c6\u53ca\u56fe\u50cf\u878d\u5408\u56db\u4e2a\u65b9\u9762\u3002<\/p>\n\n\n\n<p>\u533b\u5b66\u56fe\u50cf\u6570\u636e\u5177\u6709\u53ef\u83b7\u5f97\u3001\u8d28\u91cf\u9ad8\u3001\u4f53\u91cf\u5927\u3001\u6807\u51c6\u7edf\u4e00\u7b49\u7279\u70b9\uff0c\u4f7f\u4eba\u5de5\u667a\u80fd\u5728\u5176\u4e2d\u7684\u5e94\u7528\u8f83\u4e3a\u6210\u719f\u3002\u5229\u7528\u56fe\u50cf\u5904\u7406\u6280\u672f\u5bf9\u56fe\u50cf\u8fdb\u884c\u5206\u6790\u548c\u5904\u7406\uff0c\u5b9e\u73b0\u5bf9\u4eba\u4f53\u5668\u5b98\u3001\u8f6f\u7ec4\u7ec7\u548c\u75c5\u53d8\u4f53\u7684\u4f4d\u7f6e\u68c0\u6d4b\u3001\u5206\u5272\u63d0\u53d6\u3001\u4e09\u7ef4\u91cd\u5efa\u548c\u4e09\u7ef4\u663e\u793a\uff0c\u53ef\u4ee5\u5bf9\u611f\u5174\u8da3\u533a\u57df\uff08Region of Interest, ROI)\u8fdb\u884c\u5b9a\u6027\u751a\u81f3\u5b9a\u91cf\u7684\u5206\u6790\uff0c\u4ece\u800c\u5927\u5927\u63d0\u9ad8\u4e34\u5e8a\u8bca\u65ad\u7684\u6548\u7387\u3001\u51c6\u786e\u6027\u548c\u53ef\u9760\u6027\uff0c\u5728\u533b\u7597\u6559\u5b66\u3001\u624b\u672f\u89c4\u5212\u3001\u624b\u672f\u4eff\u771f\u53ca\u5404\u79cd\u533b\u5b66\u7814\u7a76\u4e2d\u4e5f\u80fd\u8d77\u91cd\u8981\u7684\u8f85\u52a9\u4f5c\u7528\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u4e8c\u3001\u533b\u5b66\u56fe\u50cf\u5904\u7406\u7684\u4e3b\u8981\u4efb\u52a1<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">2.1 \u56fe\u50cf\u68c0\u6d4b<\/h3>\n\n\n\n<p>\u56fe\u50cf\u68c0\u6d4b\u662f\u8ba1\u7b97\u673a\u8f85\u52a9\u68c0\u6d4b\u7684\u57fa\u7840\uff0c\u5e76\u4e14\u975e\u5e38\u9002\u5408\u5f15\u5165\u6df1\u5ea6\u5b66\u4e60\u3002\u533b\u5b66\u56fe\u50cf\u68c0\u6d4b\u7684\u4f20\u7edf\u65b9\u6cd5\u662f\u901a\u8fc7\u76d1\u7763\u65b9\u6cd5\u6216\u4f20\u7edf\u6570\u5b57\u56fe\u50cf\u5904\u7406\u6280\u672f\u68c0\u6d4b\u5019\u9009\u75c5\u53d8\u4f4d\u7f6e\u3002\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u65b9\u5f0f\u662f\u57fa\u4e8e\u5f71\u50cf\u5b66\u6570\u636e\u6216\u7406\u8bba\u6307\u5bfc\uff0c\u8bad\u7ec3\u7f51\u7edc\uff0c\u53d1\u73b0\u75c5\u53d8\uff0c\u63d0\u9ad8\u8bca\u65ad\u51c6\u786e\u7387\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2.2 \u56fe\u50cf\u5206\u5272<\/h3>\n\n\n\n<p>\u76ee\u524d\u533b\u5b66\u56fe\u50cf\u5206\u5272\u5904\u7406\u7684\u5bf9\u8c61\u4e3b\u8981\u662f\u5404\u79cd\u7ec6\u80de\u3001\u7ec4\u7ec7\u3001\u5668\u5b98\u7684\u56fe\u50cf\uff0c\u533b\u5b66\u56fe\u50cf\u5206\u5272\u7684\u8fc7\u7a0b\u662f\uff1a\u6839\u636e\u533a\u57df\u95f4\u7684\u76f8\u4f3c\u6216\u4e0d\u540c\uff0c\u628a\u56fe\u50cf\u5206\u5272\u6210\u82e5\u5e72\u533a\u57df\u3002<\/p>\n\n\n\n<p>\u4f20\u7edf\u7684\u56fe\u50cf\u5206\u5272\u6280\u672f\u6709\u57fa\u4e8e\u533a\u57df\u7684\u5206\u5272\u65b9\u6cd5\u548c\u57fa\u4e8e\u8fb9\u754c\u7684\u5206\u5272\u65b9\u6cd5\uff0c\u524d\u8005\u4f9d\u8d56\u4e8e\u56fe\u50cf\u7684\u7a7a\u95f4\u5c40\u90e8\u7279\u5f81\uff0c\u5982\u7070\u5ea6\u3001\u7eb9\u7406\u53ca\u5176\u5b83\u50cf\u7d20\u7edf\u8ba1\u7279\u6027\u7684\u5747\u5300\u6027\u7b49\uff0c\u540e\u8005\u4e3b\u8981\u662f\u5229\u7528\u68af\u5ea6\u4fe1\u606f\u786e\u5b9a\u76ee\u6807\u7684\u8fb9\u754c\u3002<\/p>\n\n\n\n<p>\u7ed3\u5408\u7279\u5b9a\u7684\u7406\u8bba\u5de5\u5177\uff0c\u56fe\u50cf\u5206\u5272\u6280\u672f\u6709\u4e86\u66f4\u8fdb\u4e00\u6b65\u7684\u53d1\u5c55\u3002\u6bd4\u5982\u57fa\u4e8e\u4e09\u7ef4\u53ef\u89c6\u5316\u7cfb\u7edf\u7ed3\u5408FastMarching\u7b97\u6cd5\u548cWatershed \u53d8\u6362\u7684\u533b\u5b66\u56fe\u50cf\u5206\u5272\u65b9\u6cd5\uff0c\u80fd\u5f97\u5230\u5feb\u901f\u3001\u51c6\u786e\u7684\u5206\u5272\u7ed3\u679c[1]\u3002<\/p>\n\n\n\n<p>\u968f\u7740\u5176\u5b83\u65b0\u5174\u5b66\u79d1\u7684\u53d1\u5c55\uff0c\u4ea7\u751f\u4e86\u4e00\u4e9b\u5168\u65b0\u7684\u56fe\u50cf\u5206\u5272\u6280\u672f\u3002\u5982\u57fa\u4e8e\u7edf\u8ba1\u5b66\u7684\u65b9\u6cd5\u3001\u57fa\u4e8e\u6a21\u7cca\u7406\u8bba\u7684\u65b9\u6cd5\u3001\u57fa\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u65b9\u6cd5\u3001\u57fa\u4e8e\u5c0f\u6ce2\u5206\u6790\u7684\u65b9\u6cd5\u3001\u7ec4\u5408\u4f18\u5316\u6a21\u578b\u7b49\u65b9\u6cd5\u3002<\/p>\n\n\n\n<p>\u867d\u7136\u4e0d\u65ad\u6709\u65b0\u7684\u5206\u5272\u65b9\u6cd5\u88ab\u63d0\u51fa\uff0c\u4f46\u7ed3\u679c\u90fd\u4e0d\u662f\u5f88\u5b8c\u7f8e\u3002\u76ee\u524d\u533b\u5b66\u56fe\u50cf\u5206\u5272\u65b9\u6cd5\u7684\u7814\u7a76\u5177\u6709\u5982\u4e0b\u663e\u8457\u7279\u70b9\uff1a\u73b0\u6709\u4efb\u4f55\u4e00\u79cd\u5355\u72ec\u7684\u56fe\u50cf\u5206\u5272\u7b97\u6cd5\u90fd\u96be\u4ee5\u5bf9\u4e00\u822c\u56fe\u50cf\u53d6\u5f97\u6bd4\u8f83\u6ee1\u610f\u7684\u7ed3\u679c\uff0c\u8981\u66f4\u52a0\u6ce8\u91cd\u591a\u79cd\u5206\u5272\u7b97\u6cd5\u7684\u6709\u6548\u7ed3\u5408\u3002\u5728\u76ee\u524d\u65e0\u6cd5\u5b8c\u5168\u7531\u8ba1\u7b97\u673a\u6765\u5b8c\u6210\u56fe\u50cf\u5206\u5272\u4efb\u52a1\u7684\u60c5\u51b5\u4e0b\uff0c\u4eba\u673a\u4ea4\u4e92\u5f0f\u5206\u5272\u65b9\u6cd5\u9010\u6e10\u6210\u4e3a\u7814\u7a76\u91cd\u70b9\uff0c\u9664\u6b64\u4e4b\u5916\uff0c\u5206\u5272\u65b9\u6cd5\u7684\u7814\u7a76\u91cd\u70b9\u4e3b\u8981\u662f\uff1a\u81ea\u52a8\u3001\u7cbe\u786e\u3001\u5feb\u901f\u3001\u81ea\u9002\u5e94\u3001\u9c81\u68d2\u6027\u3001\u591a\u6a21\u6001\u878d\u5408\u7b49\u65b9\u5411\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2.3 \u56fe\u50cf\u914d\u51c6<\/h3>\n\n\n\n<p>\u56fe\u50cf\u914d\u51c6\u662f\u56fe\u50cf\u878d\u5408\u7684\u524d\u63d0\uff0c\u662f\u516c\u8ba4\u96be\u5ea6\u8f83\u5927\u7684\u56fe\u50cf\u5904\u7406\u6280\u672f\uff0c\u4e5f\u662f\u51b3\u5b9a\u533b\u5b66\u56fe\u50cf\u878d\u5408\u6280\u672f\u53d1\u5c55\u7684\u5173\u952e\u6280\u672f\u3002<\/p>\n\n\n\n<p>\u5728\u4e34\u5e8a\u8bca\u65ad\u4e2d\uff0c\u5355\u4e00\u6a21\u6001\u7684\u5355\u5f20\u56fe\u50cf\u5f80\u5f80\u4e0d\u80fd\u63d0\u4f9b\u533b\u751f\u6240\u9700\u8981\u7684\u8db3\u591f\u4fe1\u606f\uff0c\u56e0\u6b64\uff0c\u533b\u751f\u7ecf\u5e38\u9700\u8981\u5c06\u591a\u79cd\u6a21\u5f0f\u6216\u540c\u4e00\u6a21\u5f0f\u7684\u591a\u6b21\u6210\u50cf\u914d\u51c6\u878d\u5408\uff0c\u4ece\u800c\u5b9e\u73b0\u611f\u5174\u8da3\u533a\u57df\u7684\u4fe1\u606f\u4e92\u8865\u3002\u6839\u636e\u60a3\u8005\u591a\u65b9\u9762\u7684\u7efc\u5408\u4fe1\u606f\uff0c\u533b\u751f\u624d\u80fd\u505a\u51fa\u66f4\u52a0\u51c6\u786e\u7684\u8bca\u65ad\u6216\u5236\u5b9a\u51fa\u66f4\u52a0\u5408\u9002\u60a3\u8005\u7684\u6cbb\u7597\u65b9\u6cd5[2]\u3002<\/p>\n\n\n\n<p>\u56fe\u50cf\u914d\u51c6\u5c31\u662f\u8981\u5bf9\u51e0\u5e45\u56fe\u50cf\u4f5c\u5b9a\u91cf\u5206\u6790\uff0c\u9996\u5148\u9700\u8981\u89e3\u51b3\u56fe\u50cf\u4e4b\u95f4\u7684\u4e25\u683c\u5bf9\u9f50\u95ee\u9898\u3002\u533b\u5b66\u56fe\u50cf\u914d\u51c6\u5305\u62ec\u56fe\u50cf\u7684\u5b9a\u4f4d\u548c\u8f6c\u6362\uff0c\u5373\u901a\u8fc7\u5bfb\u627e\u4e00\u79cd\u7a7a\u95f4\u53d8\u6362\u4f7f\u4e24\u5e45\u56fe\u50cf\u5bf9\u5e94\u70b9\u8fbe\u5230\u7a7a\u95f4\u4f4d\u7f6e\u548c\u89e3\u5256\u7ed3\u6784\u4e0a\u7684\u5b8c\u5168\u4e00\u81f4\u3002\u914d\u51c6\u7684\u7ed3\u679c\u5e94\u8be5\u81f3\u5c11\u4f7f\u6709\u8bca\u65ad\u610f\u4e49\u7684\u70b9\uff0c\u53ca\u624b\u672f\u611f\u5174\u8da3\u7684\u70b9\u8fbe\u5230\u5339\u914d\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2.4 \u56fe\u50cf\u878d\u5408<\/h3>\n\n\n\n<p>\u56fe\u50cf\u878d\u5408\u7684\u4e3b\u8981\u76ee\u7684\u662f\u901a\u8fc7\u5bf9\u591a\u5e45\u56fe\u50cf\u95f4\u7684\u5197\u4f59\u6570\u636e\u7684\u5904\u7406\u6765\u63d0\u9ad8\u56fe\u50cf\u7684\u53ef\u8bfb\u6027\uff0c\u5bf9\u591a\u5e45\u56fe\u50cf\u95f4\u7684\u4e92\u8865\u4fe1\u606f\u7684\u5904\u7406\u6765\u63d0\u9ad8\u56fe\u50cf\u7684\u6e05\u6670\u5ea6\u3002\u591a\u6a21\u6001\u533b\u5b66\u56fe\u50cf\u7684\u878d\u5408\u628a\u6709\u4ef7\u503c\u7684\u751f\u7406\u529f\u80fd\u4fe1\u606f\u4e0e\u7cbe\u786e\u7684\u89e3\u5256\u7ed3\u6784\u7ed3\u5408\u5728\u4e00\u8d77\uff0c\u53ef\u4ee5\u4e3a\u4e34\u5e8a\u63d0\u4f9b\u66f4\u52a0\u5168\u9762\u548c\u51c6\u786e\u7684\u8d44\u6599[3]\u3002<\/p>\n\n\n\n<p>\u56fe\u50cf\u6570\u636e\u878d\u5408\u4e3b\u8981\u6709\u4ee5\u50cf\u7d20\u4e3a\u57fa\u7840\u7684\u65b9\u6cd5\u548c\u4ee5\u56fe\u50cf\u7279\u5f81\u4e3a\u57fa\u7840\u7684\u65b9\u6cd5\u3002\u524d\u8005\u662f\u5bf9\u56fe\u50cf\u8fdb\u884c\u9010\u70b9\u5904\u7406\uff0c\u628a\u4e24\u5e45\u56fe\u50cf\u5bf9\u5e94\u50cf\u7d20\u70b9\u7684\u7070\u5ea6\u503c\u8fdb\u884c\u52a0\u6743\u6c42\u548c\u3001\u7070\u5ea6\u53d6\u5927\u6216\u8005\u7070\u5ea6\u53d6\u5c0f\u7b49\u64cd\u4f5c\uff0c\u7b97\u6cd5\u5b9e\u73b0\u6bd4\u8f83\u7b80\u5355\uff0c\u4e0d\u8fc7\u5b9e\u73b0\u6548\u679c\u548c\u6548\u7387\u90fd\u76f8\u5bf9\u8f83\u5dee\uff0c\u878d\u5408\u540e\u56fe\u50cf\u4f1a\u51fa\u73b0\u4e00\u5b9a\u7a0b\u5ea6\u7684\u6a21\u7cca\u3002\u540e\u8005\u8981\u5bf9\u56fe\u50cf\u8fdb\u884c\u7279\u5f81\u63d0\u53d6\u7b49\u5904\u7406\uff0c\u7528\u5230\u7684\u7b97\u6cd5\u539f\u7406\u590d\u6742\uff0c\u5b9e\u73b0\u6548\u679c\u6bd4\u8f83\u7406\u60f3\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u4e09\u3001\u533b\u5b66\u56fe\u50cf\u6570\u636e\u7684\u4ecb\u7ecd<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">3.1 \u6570\u636e\u7684\u83b7\u53d6<\/h3>\n\n\n\n<p>\u533b\u5b66\u56fe\u50cf\u7684\u76ee\u7684\u662f\u4f7f\u89c2\u5bdf\u8005\u770b\u5230\u60a3\u8005\u4f53\u5185\u7684\u7269\u4f53\u6216\u72b6\u51b5\uff0c\u56e0\u6b64\u533b\u5b66\u56fe\u50cf\u5fc5\u987b\u5448\u73b0\u7279\u5b9a\u89e3\u5256\u7279\u5f81\u7684\uff0c\u8fd9\u53d6\u51b3\u4e8e\u6210\u50cf\u7cfb\u7edf\u7684\u7279\u6027\u53ca\u5176\u64cd\u4f5c\u65b9\u5f0f\uff0c\u5927\u591a\u6570\u533b\u5b66\u6210\u50cf\u7cfb\u7edf\u5177\u6709\u76f8\u5f53\u591a\u7684\u64cd\u4f5c\u53d8\u91cf\uff0c\u5b83\u4eec\u53ef\u4ee5\u662f\u53ef\u53d8\u7cfb\u7edf\u7ec4\u4ef6\uff0c\u4f8b\u5982\uff1a\u78c1\u5171\u632f\u6210\u50cf\uff08MRI\uff09\u4e2d\u7684\u7ebf\u5708\uff0c\u6216\u8005\u662f\u4e0e\u6210\u50cf\u8fc7\u7a0b\u76f8\u5173\u7684\u53ef\u8c03\u8282\u7269\u7406\u91cf\uff0c\u4f8b\u5982\uff1aMRI\u4e2d\u7684\u56de\u58f0\u65f6\u95f4\uff08TE\uff09\u3002\u9009\u62e9\u7684\u503c\u5c06\u51b3\u5b9a\u56fe\u50cf\u7684\u8d28\u91cf\u548c\u770b\u5230\u7684\u7279\u5b9a\u89e3\u5256\u7279\u5f81\u3002<\/p>\n\n\n\n<p>\u533b\u5b66\u56fe\u50cf\u901a\u5e38\u90fd\u662f\u60a3\u8005\u7684\u771f\u5b9e\u6570\u636e\u8d44\u6599\uff0c\u5982\u679c\u9700\u8981\u83b7\u53d6\uff0c\u5927\u5bb6\u53ef\u4ee5\u5bfb\u627e\u516c\u5f00\u6570\u636e\u5e93\u7684\u8d44\u6599\u3002\u73b0\u5728\u5f88\u591a\u673a\u6784\u4e5f\u4e3e\u884c\u4e86\u533b\u5b66\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u6bd4\u8d5b\uff0c\u533b\u5b66\u5f71\u50cf\u7684\u7814\u7a76\u8d44\u6599\u5728\u7f51\u7edc\u4e0a\u5df2\u7ecf\u5f88\u5e38\u89c1\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3.2 \u56fe\u50cf\u6570\u636e\u7684\u7c7b\u578b<\/h3>\n\n\n\n<p>\u533b\u5b66\u56fe\u50cf\u5904\u7406\u7684\u5bf9\u8c61\u662f\u5404\u79cd\u4e0d\u540c\u6210\u50cf\u673a\u7406\u7684\u533b\u5b66\u5f71\u50cf\uff0c\u4e34\u5e8a\u5e7f\u6cdb\u4f7f\u7528\u7684\u533b\u5b66\u6210\u50cf\u79cd\u7c7b\u4e3b\u8981\u6709\uff1aX-\u5c04\u7ebf\u6210\u50cf \uff08X-CT\uff09\u3001\u7535\u8111\u65ad\u5c42\u626b\u63cf\uff08CT\uff09\u3001\u6b63\u7535\u5b50\u53d1\u5c04\u8ba1\u7b97\u673a\u65ad\u5c42\u663e\u50cf\uff08PET-CT\uff09\u3001\u6838\u78c1\u5171\u632f\u6210\u50cf\uff08MRI\uff09\u3001\u6838\u533b\u5b66\u6210\u50cf\uff08NMI\uff09\u3001\u8d85\u58f0\u6ce2\u6210\u50cf\uff08UI\uff09\u3001\u663e\u5fae\u955c\u4e0b\u62cd\u6444\u7684\u75c5\u7406\u56fe\u50cf\u7b49\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3.3 \u6570\u636e\u683c\u5f0f\u7684\u6807\u51c6<\/h3>\n\n\n\n<p>DICOM\uff08Digital Imaging and Communications in Medicine\uff09\u5373\u533b\u5b66\u6570\u5b57\u6210\u50cf\u548c\u901a\u4fe1\uff0c\u662f\u533b\u5b66\u56fe\u50cf\u548c\u76f8\u5173\u4fe1\u606f\u7684\u56fd\u9645\u6807\u51c6\u3002\u8fd9\u4e5f\u662f\u76ee\u524d\u5e94\u7528\u6700\u4e3a\u5e7f\u6cdb\u7684\u533b\u5b66\u5f71\u50cf\u683c\u5f0f\uff0c\u5e38\u89c1\u7684CT,\u6838\u78c1\u5171\u632f\uff0c\u5fc3\u8840\u7ba1\u6210\u50cf\u7b49\u5927\u591a\u91c7\u7528Dicom\u683c\u5f0f\u7684\u5b58\u50a8\u3002<\/p>\n\n\n\n<p>doicm\u4e3b\u8981\u5b58\u50a8\u4e24\u65b9\u9762\u4fe1\u606f\uff1a\u5173\u4e8e\u60a3\u8005\u7684PHI(Protected Health Imformation)\u4fe1\u606f\u548c\u56fe\u50cf\u4fe1\u606f\u3002PHI\u5c31\u662f\u60a3\u8005\u7684\u76f8\u5173\u4fe1\u606f\u3002\u4f8b\u5982\uff1a\u59d3\u540d\uff0c\u6027\u522b\uff0c\u5e74\u9f84\uff0c\u7ee7\u5f80\u75c5\u5386\u7b49\u3002\u56fe\u50cf\u4fe1\u606f\u5305\u62ec\u4e24\u90e8\u5206\uff0c\u4e00\u90e8\u5206\u4fe1\u606f\u662f\u626b\u63cf\u8fc7\u540e\u60a3\u8005\u56fe\u50cf\u7684\u67d0\u4e00\u5c42\u5207\u7247\uff0c\u533b\u751f\u901a\u8fc7\u4e13\u95e8\u7684Dicom\u9605\u8bfb\u5668\u6253\u5f00\uff0c\u5bdf\u770b\u60a3\u8005\u75c5\u60c5\u3002\u53e6\u4e00\u90e8\u5206\u662f\u76f8\u5173\u7684\u8bbe\u5907\u4fe1\u606f\uff0c\u4f8b\u5982\u751f\u4ea7\u7684Dicom\u56fe\u50cf\u662fX\u5149\u673a\u626b\u63cf\u51fa\u7684X\u5149\u56fe\u50cf\u7684\u67d0\u4e00\u5c42\uff0c\u90a3\u4e48Dicom\u5c31\u4f1a\u5b58\u50a8\u5173\u4e8e\u6b64X\u5149\u673a\u7684\u76f8\u5173\u8bbe\u5907\u4fe1\u606f\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u56db\u3001\u533b\u5b66\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u7684\u8bc4\u4ef7\u6307\u6807<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">4.1 \u4ea4\u5e76\u6bd4<\/h3>\n\n\n\n<p>\u4ea4\u5e76\u6bd4\uff08Intersection over Unoin, IoU\uff09\u662f\u68c0\u6d4b\u7ed3\u679c\u7684\u77e9\u5f62\u6846\u4e0e\u6837\u672c\u6807\u6ce8\u7684\u77e9\u5f62\u6846\u7684\u4ea4\u96c6\u4e0e\u5e76\u96c6\u9762\u79ef\u7684\u6bd4\u503c\u3002\u4e00\u822c\u5bf9\u4e8e\u68c0\u6d4b\u6846\u7684\u5224\u5b9a\u90fd\u4f1a\u5b58\u5728\u4e00\u4e2a\u9608\u503c\uff0c\u5e38\u89c1\u7684\u9608\u503c\u4e3a0.5\uff0c\u5f53\u8ba1\u7b97\u5f97\u5230\u7684IoU\u5927\u4e8e0.5\u65f6\u53ef\u4ee5\u8ba4\u4e3a\u68c0\u6d4b\u5230\u76ee\u6807\u7269\u4f53\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4.2 \u56db\u79cd\u7ed3\u679c\u53ca\u5176\u5f15\u7533\u6307\u6807<\/h3>\n\n\n\n<p>\u5b9e\u9645\u4efb\u52a1\u4e2d\u7684\u5206\u7c7b\u4efb\u52a1\u5e38\u5e38\u4f5c\u4e3a\u68c0\u6d4b\u4efb\u52a1\u540e\u7684\u4e00\u4e2a\u5c0f\u4efb\u52a1\uff0c\u4f46\u4ed6\u7684\u8bc4\u4ef7\u6307\u6807\u8f83\u591a\uff0c\u56e0\u6b64\u5355\u72ec\u5728\u672c\u8282\u4e2d\u5217\u51fa<\/p>\n\n\n\n<p>\u9996\u5148\u8981\u8bf4\u660e\uff0c\u4ece\u6210\u50cf\u8fc7\u7a0b\u5f97\u51fa\u7684\u8bca\u65ad\u5c06\u75c5\u4f8b\u5206\u4e3a\u56db\u7c7b\uff1a\u5b9e\u9645\u662f\u9633\u6027\u5e76\u88ab\u9884\u6d4b\u6b63\u786e\uff0c\u5373\u4e3a\u771f\u9633\u6027\uff08True Positive, TP\uff09\uff0c\u5b9e\u9645\u662f\u9634\u6027\u5e76\u88ab\u9884\u6d4b\u6b63\u786e\uff0c\u5373\u4e3a\u771f\u9634\u6027\uff08True Negative, TN\uff09\uff0c\u5b9e\u9645\u662f\u9633\u6027\u5e76\u88ab\u9884\u6d4b\u9519\u8bef\uff0c\u5373\u4e3a\u5047\u9633\u6027\uff08False Positive, FP\uff09\u548c\u5b9e\u9645\u662f\u9634\u6027\u5e76\u88ab\u9884\u6d4b\u9519\u8bef\uff0c\u5373\u4e3a\u5047\u9634\u6027\uff08False Negative, FN\uff09\uff0c\u56db\u79cd\u7ed3\u679c\u5982\u4e0b\u8868\u6240\u793a\uff0c\u5176\u4e2d1\u4ee3\u8868\u9633\u6027\u548c\u6b63\u786e\uff0c0\u4ee3\u8868\u9634\u6027\u548c\u9519\u8bef\u3002\u5927\u90e8\u5206\u533b\u5b66\u56fe\u50cf\u5904\u7406\u4efb\u52a1\u8bc4\u4ef7\u6307\u6807\uff0c\u90fd\u53ef\u4ee5\u7528\u8fd9\u56db\u4e2a\u7ed3\u679c\u8ba1\u7b97\u5f97\u51fa\u3002<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" src=\"https:\/\/pic2.zhimg.com\/80\/v2-13718a220113f367dbcb02201cf3cea1_1440w.webp\" alt=\"\"\/><\/figure>\n\n\n\n<p>\u5728\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u53ea\u6709\u771f\u9633\u6027\u548c\u771f\u9634\u6027\u75c5\u4f8b\u3002\u51fa\u4e8e\u591a\u79cd\u539f\u56e0\u51fa\u73b0\u5047\u9634\u6027\u548c\u5047\u9633\u6027\uff0c\u5305\u62ec\u7279\u5b9a\u6210\u50cf\u65b9\u6cd5\u7684\u56fa\u6709\u9650\u5236\uff0c\u56fe\u50cf\u5904\u7406\u65b9\u5f0f\u9650\u5236\u3002<\/p>\n\n\n\n<p>\u51c6\u786e\u7387\uff08accuracy\uff09\u662f\u5206\u7c7b\u4efb\u52a1\u7684\u5e38\u89c1\u8bc4\u4ef7\u6307\u6807\uff0c\u662f\u5206\u7c7b\u6b63\u786e\u7684\u6837\u672c\u6570\u9664\u4ee5\u6240\u6709\u6837\u672c\u6570\uff0c\u5373\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>accuracy = (TP+TN)\/(TP+TN+FP+FN)<\/code><\/pre>\n\n\n\n<p>\u53ec\u56de\u7387\uff08recall\uff09\u4e5f\u53eb\u505a\u7075\u654f\u5ea6\uff08True Positive Rate\uff09\uff0c\u6307\u5728\u603b\u7684\u6b63\u6837\u672c\u4e2d\uff0c\u627e\u56de\u4e86\u591a\u5c11\u6b63\u6837\u672c\uff0c\u5373\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>recall = TP\/(TP+FN)<\/code><\/pre>\n\n\n\n<p>F1\u5206\u6570(F1-score)\u8ba4\u4e3a\u53ec\u56de\u7387\u548c\u7cbe\u5ea6\u540c\u7b49\u91cd\u8981, \u4e00\u4e9b\u591a\u5206\u7c7b\u95ee\u9898\u7684\u673a\u5668\u5b66\u4e60\u7ade\u8d5b\uff0c\u5e38\u5e38\u5c06F1-score\u4f5c\u4e3a\u6700\u7ec8\u6d4b\u8bc4\u7684\u65b9\u6cd5\u3002\u5b83\u662f\u7cbe\u786e\u7387\u548c\u53ec\u56de\u7387\u7684\u8c03\u548c\u5e73\u5747\u6570\uff0c\u6700\u5927\u4e3a1\uff0c\u6700\u5c0f\u4e3a0\u3002\u8ba1\u7b97\u516c\u5f0f\u5982\u4e0b\uff1a<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>F1 = 2TP\/(2TP+FP+FN)<\/code><\/pre>\n\n\n\n<p>\u53d7\u8bd5\u8005\u5de5\u4f5c\u7279\u5f81\u66f2\u7ebf\uff08Receiver Operating Characteristic Curve, ROC\uff09\u6a2a\u8f74\u4e3aFP\uff0c\u7eb5\u8f74\u4e3aTP\uff0c\u66f2\u7ebf\u63cf\u8ff0\u7684\u5176\u5b9e\u662f\u5206\u7c7b\u5668\u6027\u80fd\u968f\u7740\u5206\u7c7b\u5668\u9608\u503c\u7684\u53d8\u5316\u800c\u53d8\u5316\u7684\u8fc7\u7a0b\u3002<\/p>\n\n\n\n<p>\u7406\u60f3\u7684\u7b97\u6cd5\u4ea7\u751f100\uff05\u7684\u7075\u654f\u5ea6\u548c100\uff05\u7684\u7279\u5f02\u6027\uff0c\u6210\u50cf\u65b9\u6cd5\u7684\u7279\u5f81\u548c\u6240\u5f97\u56fe\u50cf\u7684\u8d28\u91cf\u51b3\u5b9a\u4e86\u5b9e\u9645\u66f2\u7ebf\u7684\u5f62\u72b6\u4ee5\u53ca\u7279\u5b9a\u75c5\u7406\u72b6\u51b5\u7684\u7075\u654f\u5ea6\u548c\u7279\u5f02\u6027\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u89c2\u5bdf\u8005\u7528\u4e8e\u8fdb\u884c\u8bca\u65ad\u7684\u6807\u51c6\u786e\u5b9a\u66f2\u7ebf\u4e0a\u4ea7\u751f\u5b9e\u9645\u7075\u654f\u5ea6\u548c\u7279\u5f02\u6027\u503c\u7684\u70b9\u3002\u6709\u5173ROC\u66f2\u7ebf\u7684\u66f4\u591a\u7406\u8bba\u7ec6\u8282\uff0c\u53ef\u4ee5\u67e5\u770b\u5b66\u4e60\u8d44\u6599[4]\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4.3 \u5176\u4ed6<\/h3>\n\n\n\n<p>\u533b\u5b66\u56fe\u50cf\u5206\u5272\u4e0e\u914d\u51c6\u6307\u6807\u8f83\u5c11\uff0c\u5206\u5272\u7cbe\u5ea6\u5c31\u662f\u5206\u5272\u51c6\u786e\u9762\u79ef\u4e0e\u6807\u6ce8\u7684\u771f\u5b9e\u5206\u5272\u9762\u79ef\u4e4b\u6bd4\u3002\u914d\u51c6\u7684\u6307\u6807\u4e3b\u8981\u662f\u914d\u51c6\u56fe\u50cf\u7684\u50cf\u7d20\u4e0e\u6807\u6ce8\u56fe\u50cf\u50cf\u7d20\u7684\u7269\u7406\u8ddd\u79bb\u3002<\/p>\n\n\n\n<p>\u533b\u5b66\u56fe\u50cf\u878d\u5408\u7684\u6307\u6807\u4e3b\u8981\u6709\u4ee5\u4e0b\u8fd9\u4e9b\uff1a\u7a7a\u95f4\u9891\u7387\uff0c\u53cd\u6620\u56fe\u50cf\u7070\u5ea6\u53d8\u5316\uff0c\u5e73\u5747\u68af\u5ea6\uff0c\u8861\u91cf\u56fe\u50cf\u7684\u6e05\u6670\u7a0b\u5ea6\uff0c\u5e73\u5747\u68af\u5ea6\u8d8a\u5927\uff0c\u56fe\u50cf\u6e05\u6670\u5ea6\u8d8a\u597d\u3002\u4e92\u4fe1\u606f\uff0c\u5ea6\u91cf\u878d\u5408\u56fe\u50cf\u4e0e\u8f93\u5165\u56fe\u50cf\u5728\u7070\u5ea6\u5206\u5e03\u4e0a\u7684\u76f8\u4f3c\u7a0b\u5ea6\uff0c\u5373\u878d\u5408\u56fe\u50cf\u4fdd\u7559\u539f\u56fe\u50cf\u4fe1\u606f\u7684\u591a\u5c11\u3002\u5982\u679c\u8fd8\u60f3\u4e86\u89e3\u66f4\u591a\u6307\u6807\uff0c\u53ef\u4ee5\u52a8\u624b\u641c\u7d22\u76f8\u5173\u6587\u732e\u4e86\u89e3\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u4e94\u3001\u533b\u5b66\u56fe\u50cf\u5904\u7406\u9886\u57df\u7684\u6311\u6218<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">5.1 \u6570\u636e\u7ef4\u5ea6\u95ee\u9898<\/h3>\n\n\n\n<p>\u5728\u8fc4\u4eca\u4e3a\u6b62\u7684\u5927\u591a\u6570\u5de5\u4f5c\u4e2d\uff0c\u662f\u57282D\u56fe\u50cf\u4e2d\u8fdb\u884c\u5904\u7406\u5206\u6790\uff0c\u76ee\u524d\u6709\u8d8a\u6765\u8d8a\u591a\u7684\u4eba\u8f6c\u54113D\u6570\u636e\u5904\u7406\u7684\u7814\u7a76\uff0c\u5176\u4e2d\u5b58\u5728\u5f88\u591a\u65b0\u7684\u95ee\u9898\u548c\u6311\u6218\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5.2 \u5b66\u4e60\u65b9\u6cd5<\/h3>\n\n\n\n<p>\u5f53\u6211\u4eec\u67e5\u770b\u7f51\u7edc\u6587\u732e\u65f6\uff0c\u5927\u591a\u6570\u5de5\u4f5c\u90fd\u96c6\u4e2d\u5728\u53d7\u76d1\u7763\u7684CNN\u4e0a\uff0c\u8fd9\u79cd\u7f51\u7edc\u5bf9\u4e8e\u8bb8\u591a\u5e94\u7528\u662f\u91cd\u8981\u7684\uff0c\u5305\u62ec\u68c0\u6d4b\uff0c\u5206\u5272\u548c\u6807\u8bb0\u3002\u56e0\u6b64\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u65b9\u6cd5\u4ecd\u7136\u662f\u76ee\u524d\u6700\u70ed\u95e8\u7684\u65b9\u6cd5\uff0c\u800c\u5176\u4e2d\u7684\u53ef\u89e3\u91ca\u6027\u548c\u65b0\u7684\u7f51\u7edc\u7ed3\u6784\u65b9\u9762\uff0c\u4ecd\u7136\u5b58\u5728\u975e\u5e38\u5927\u7684\u6311\u6218\u548c\u53ef\u53d1\u5c55\u7a7a\u95f4\u3002\u53e6\u5916\uff0c\u4ecd\u7136\u6709\u4e00\u4e9b\u7814\u7a76\u4eba\u5458\u4e13\u6ce8\u4e8e\u65e0\u76d1\u7763\u65b9\u6848\uff0c\u6709\u4e0d\u5c11\u4eba\u671f\u5f85\u7740\u65e0\u76d1\u7763\u65b9\u6848\u6709\u66f4\u597d\u7684\u8868\u73b0\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5.3 \u8fc1\u79fb\u5b66\u4e60\u548c\u5fae\u8c03<\/h3>\n\n\n\n<p>\u5728\u533b\u5b66\u6210\u50cf\u9886\u57df\u7ecf\u5e38\u9047\u5230\u6ca1\u6709\u8db3\u591f\u7684\u6570\u636e\u7684\u60c5\u51b5\uff0c\u6b64\u65f6\u53ef\u4ee5\u5c1d\u8bd5\u4e24\u79cd\u65b9\u6cd5\uff1a\u8fc1\u79fb\u5b66\u4e60\u548c\u7f51\u7edc\u5fae\u8c03\u3002\u8fc1\u79fb\u5b66\u4e60\u662f\u6307\u4ece\u81ea\u7136\u56fe\u50cf\u6570\u636e\u96c6\u6216\u4e0d\u540c\u533b\u5b66\u9886\u57df\u9884\u8bad\u7ec3\u7684\u7f51\u7edc\u6a21\u578b\u7528\u4e8e\u65b0\u7684\u533b\u7597\u4efb\u52a1\u3002\u5728\u4e00\u4e2a\u65b9\u6848\u4e2d\uff0c\u9884\u5148\u8bad\u7ec3CNN\u5e94\u7528\u4e8e\u8f93\u5165\u56fe\u50cf\uff0c\u7136\u540e\u4ece\u7f51\u7edc\u5c42\u63d0\u53d6\u8f93\u51fa\u3002\u63d0\u53d6\u7684\u8f93\u51fa\u88ab\u8ba4\u4e3a\u662f\u7279\u5f81\u5e76\u4e14\u7528\u4e8e\u8bad\u7ec3\u5355\u72ec\u7684\u6a21\u5f0f\u5206\u7c7b\u5668\u3002\u7f51\u7edc\u5fae\u8c03\u662f\u6307\u5f53\u624b\u5934\u7684\u4efb\u52a1\u786e\u5b9e\u5b58\u5728\u4e2d\u7b49\u5927\u5c0f\u7684\u6570\u636e\u96c6\u65f6\uff0c\u4f7f\u7528\u9884\u5148\u8bad\u7ec3\u7684CNN\u4f5c\u4e3a\u7f51\u7edc\u7684\u521d\u59cb\u5316\uff0c\u7136\u540e\u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u76d1\u7763\u8bad\u7ec3\uff0c\u5176\u4e2d\u51e0\u4e2a\uff08\u6216\u5168\u90e8\uff09\u7f51\u7edc\u5c42\uff0c\u4f7f\u7528\u4efb\u52a1\u7684\u65b0\u6570\u636e\u3002<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5.4 \u6570\u636e\u9690\u79c1<\/h3>\n\n\n\n<p>\u53d7\u793e\u4f1a\u548c\u6280\u672f\u95ee\u9898\u7684\u5f71\u54cd\uff0c\u9700\u8981\u4ece\u793e\u4f1a\u5b66\u548c\u6280\u672f\u5b66\u7684\u89d2\u5ea6\u5171\u540c\u89e3\u51b3\u3002\u5728\u533b\u7597\u4fdd\u5065\u6570\u636e\u4e0d\u65ad\u589e\u52a0\u7684\u540c\u65f6\uff0c\u7814\u7a76\u4eba\u5458\u9762\u4e34\u5982\u4f55\u52a0\u5bc6\u60a3\u8005\u4fe1\u606f\u4ee5\u9632\u6b62\u5176\u88ab\u4f7f\u7528\u6216\u62ab\u9732\u7684\u95ee\u9898\u3002\u4f46\u662f\u4e0d\u5408\u7406\u7684\u9650\u5236\u8bbf\u95ee\u53ef\u80fd\u4f7f\u4e34\u5e8a\u51b3\u7b56\u7f3a\u5c11\u975e\u5e38\u91cd\u8981\u7684\u4fe1\u606f\u3002<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u516d\u3001CVPR2020\u533b\u5b66\u56fe\u50cf\u5904\u7406\u7c7b\u8bba\u6587\u63a8\u8350<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">6.1 \u56fe\u50cf\u68c0\u6d4b<\/h3>\n\n\n\n<ol class=\"wp-block-list\"><li>\u534a\u76d1\u7763\u5b66\u4e60\u65b9\u6cd5 + 3D\u533b\u5b66\u56fe\u50cf\u68c0\u6d4b<\/li><\/ol>\n\n\n\n<p>FocalMix: Semi-Supervised Learning for 3D Medical Image Detection<\/p>\n\n\n\n<p>\u4f5c\u8005 | Dong Wang, Yuan Zhang, Kexin Zhang, Liwei Wang<\/p>\n\n\n\n<p>\u5355\u4f4d | \u5317\u4eac\u5927\u5b66\uff1b\u533b\u51c6\u667a\u80fd<\/p>\n\n\n\n<p>\u94fe\u63a5\uff5c<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Wang_FocalMix_Semi-Supervised_Learning_for_3D_Medical_Image_Detection_CVPR_2020_paper.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Wang_FocalMix_Semi-Supervised_Learning_for_3D_Medical_Image_Detection_CVPR_2020_paper.pdf<\/a><\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>\u4e73\u817aX\u7ebf\u68c0\u6d4b<\/li><\/ol>\n\n\n\n<p>Cross-View Correspondence Reasoning Based on Bipartite Graph Convolutional Network for Mammogram Mass Detection<\/p>\n\n\n\n<p>\u4f5c\u8005 | Yuhang Liu, Fandong Zhang, Qianyi Zhang, Siwen Wang, Yizhou Wang, Yizhou Yu<\/p>\n\n\n\n<p>\u5355\u4f4d | Deepwise AI Lab\uff1b\u5317\u5927<\/p>\n\n\n\n<p>\u94fe\u63a5 |&nbsp;<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Liu_Cross-View_Correspondence_Reasoning_Based_on_Bipartite_Graph_Convolutional_Network_for_CVPR_2020_paper.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Liu_Cross-View_Correspondence_Reasoning_Based_on_Bipartite_Graph_Convolutional_Network_for_CVPR_2020_paper.pdf<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">6.2 \u56fe\u50cf\u5206\u5272<\/h3>\n\n\n\n<ol class=\"wp-block-list\"><li>\u7528\u4e8eCT\u626b\u63cf\u4e2d\u7684\u7ba1\u72b6\u7ed3\u6784\u5206\u5272<\/li><\/ol>\n\n\n\n<p>Deep Distance Transform for Tubular Structure Segmentation in CT Scans<\/p>\n\n\n\n<p>\u4f5c\u8005 | Yan Wang, Xu Wei, Fengze Liu, Jieneng Chen, Yuyin Zhou, Wei Shen, Elliot K. Fishman, Alan L. Yuille<\/p>\n\n\n\n<p>\u5355\u4f4d | \u7ea6\u7ff0\u65af\u970d\u666e\u91d1\u65af\uff1b\u52a0\u5229\u798f\u5c3c\u4e9a\u5927\u5b66\u5723\u8fed\u6208\u5206\u6821\uff1b\u540c\u6d4e\u5927\u5b66\u7b49<\/p>\n\n\n\n<p>\u94fe\u63a5\uff5c<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Wang_Deep_Distance_Transform_for_Tubular_Structure_Segmentation_in_CT_Scans_CVPR_2020_paper.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Wang_Deep_Distance_Transform_for_Tubular_Structure_Segmentation_in_CT_Scans_CVPR_2020_paper.pdf<\/a><\/p>\n\n\n\n<ol class=\"wp-block-list\"><li>\u7528\u4e8e3D\u533b\u5b66\u56fe\u50cf\u5206\u5272<\/li><\/ol>\n\n\n\n<p>C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation<\/p>\n\n\n\n<p>\u4f5c\u8005 | Qihang Yu, Dong Yang, Holger Roth, Yutong Bai, Yixiao Zhang, Alan L. Yuille, Daguang Xu<\/p>\n\n\n\n<p>\u5355\u4f4d | \u7ea6\u7ff0\u65af\u970d\u666e\u91d1\u65af\uff1b\u82f1\u4f1f\u8fbe<\/p>\n\n\n\n<p>\u94fe\u63a5\uff5c<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Yu_C2FNAS_Coarse-to-Fine_Neural_Architecture_Search_for_3D_Medical_Image_Segmentation_CVPR_2020_paper.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Yu_C2FNAS_Coarse-to-Fine_Neural_Architecture_Search_for_3D_Medical_Image_Segmentation_CVPR_2020_paper.pdf<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">6.3 \u56fe\u50cf\u914d\u51c6<\/h3>\n\n\n\n<ol class=\"wp-block-list\"><li>\u57fa\u4e8e\u5b66\u4e60\u7684\u533b\u5b66\u56fe\u50cf\u914d\u51c6\u7684\u9ad8\u6548\u7f51\u7edc<\/li><\/ol>\n\n\n\n<p>DeepFLASH: An Efficient Network for Learning-Based Medical Image Registration<\/p>\n\n\n\n<p>\u4f5c\u8005 | Jian Wang, Miaomiao Zhang<\/p>\n\n\n\n<p>\u5355\u4f4d | \u5f17\u5409\u5c3c\u4e9a\u5927\u5b66<\/p>\n\n\n\n<p>\u94fe\u63a5\uff5c<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Wang_DeepFLASH_An_Efficient_Network_for_Learning-Based_Medical_Image_Registration_CVPR_2020_paper.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Wang_DeepFLASH_An_Efficient_Network_for_Learning-Based_Medical_Image_Registration_CVPR_2020_paper.pdf<\/a><\/p>\n\n\n\n<p>\u4ee3\u7801 |<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/github.com\/jw4hv\/deepflash\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/github.com\/jw4hv\/deepflash<\/a><\/p>\n\n\n\n<p>2.Fast Symmetric Diffeomorphic Image Registration with Convolutional Neural Networks<\/p>\n\n\n\n<p>\u4f5c\u8005 | Tony C.W. Mok, Albert C.S. Chung<\/p>\n\n\n\n<p>\u5355\u4f4d | \u9999\u6e2f\u79d1\u6280\u5927\u5b66<\/p>\n\n\n\n<p>\u8bba\u6587\uff5c<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Mok_Fast_Symmetric_Diffeomorphic_Image_Registration_with_Convolutional_Neural_Networks_CVPR_2020_paper.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/openaccess.thecvf.com\/content_CVPR_2020\/papers\/Mok_Fast_Symmetric_Diffeomorphic_Image_Registration_with_Convolutional_Neural_Networks_CVPR_2020_paper.pdf<\/a><\/p>\n\n\n\n<p>\u4ee3\u7801 |&nbsp;<a href=\"https:\/\/link.zhihu.com\/?target=https%3A\/\/github.com\/cwmok\/Fast-Symmetric-Diffeomorphic-Image-Registration-with-Convolutional-Neural-Networks\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/github.com\/cwmok\/Fast-Symmetric-Diffeomorphic-Image-Registration-with-Convolutional-Neural-Networks<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">\u4e03\u3001\u53c2\u8003\u8d44\u6599<\/h2>\n\n\n\n<p>[1]. \u6797\u7476, \u7530\u6377. \u533b\u5b66\u56fe\u50cf\u5206\u5272\u65b9\u6cd5\u7efc\u8ff0[J]. \u6a21\u5f0f\u8bc6\u522b\u4e0e\u4eba\u5de5\u667a\u80fd, 2002, 15(2).<\/p>\n\n\n\n<p>[2]. \u5468\u6c38\u65b0, \u7f57\u8ff0\u8c26. \u4e00\u79cd\u4eba\u673a\u4ea4\u4e92\u5f0f\u5feb\u901f\u8111\u56fe\u50cf\u914d\u51c6\u7cfb\u7edf[J] . \u5317\u4eac\u751f\u7269\u533b\u5b66\u5de5\u7a0b, 2002; 21 (1) \uff1a11~14<\/p>\n\n\n\n<p>[3]. \u6797\u6653, \u90b1\u6653\u5609. \u56fe\u50cf\u5206\u6790\u6280\u672f\u5728\u533b\u5b66\u4e0a\u7684\u5e94\u7528 [J] . \u5305\u5934\u533b\u5b66\u9662\u5b66\u62a5, 2005, 21 (3) \uff1a311~ 314<\/p>\n\n\n\n<p>[4]. \u674e\u5f00\u6587. ROC\u66f2\u7ebf\u7b80\u4ecb\uff3bDB\/OL]. (2017-04-11)[2021-08-05].&nbsp;<a href=\"https:\/\/zhuanlan.zhihu.com\/p\/26293316\">https:\/\/zhuanlan.zhihu.com\/p\/26293316<\/a>.\u53d1\u5e03\u4e8e 2021-10-11 15:25<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4e00\u3001\u533b\u5b66\u56fe\u50cf\u5904\u7406\u7684\u610f\u4e49 \u533b\u5b66\u56fe\u50cf&#46;&#46;&#46;<\/p>\n","protected":false},"author":1,"featured_media":1419,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-1444","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-4"],"_links":{"self":[{"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/posts\/1444","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/comments?post=1444"}],"version-history":[{"count":0,"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/posts\/1444\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/"}],"wp:attachment":[{"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/media?parent=1444"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/categories?post=1444"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sanlangcode.com\/index.php\/wp-json\/wp\/v2\/tags?post=1444"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}