{"id":2119,"date":"2024-02-05T09:01:01","date_gmt":"2024-02-05T01:01:01","guid":{"rendered":""},"modified":"2024-02-05T09:01:01","modified_gmt":"2024-02-05T01:01:01","slug":"\u533b\u5b66\u6570\u636e\u96c6","status":"publish","type":"post","link":"https:\/\/mushiming.com\/2119.html","title":{"rendered":"\u533b\u5b66\u6570\u636e\u96c6"},"content":{"rendered":"
\u6570\u636e\u96c6:\u4e00\u6587\u9053\u5c3d\u533b\u5b66\u56fe\u50cf\u6570\u636e\u96c6\u4e0e\u7ade\u8d5b\uff1a<\/p>\n
https:\/\/www.cnblogs.com\/yumoye\/p\/10512460.html<\/p>\n
https:\/\/zhuanlan.zhihu.com\/p\/24634505<\/p>\n
\u5728AI\u4e0e\u6df1\u5ea6\u5b66\u4e60\u9010\u6e10\u53d1\u5c55\u6210\u719f\u7684\u8d8b\u52bf\u4e0b\uff0c\u4eba\u5de5\u667a\u80fd\u548c\u5927\u6570\u636e\u7b49\u6280\u672f\u5f00\u59cb\u8fdb\u5165\u4e86\u533b\u7597\u9886\u57df\uff0c\u5b83\u4eec\u628a\u73b0\u6709\u7684\u4e00\u4e9b\u4f20\u7edf\u6d41\u7a0b\u8fdb\u884c\u4f18\u5316\uff0c\u5927\u5e45\u5ea6\u63d0\u9ad8\u5404\u79cd\u6d41\u7a0b\u7684\u6548\u7387\u3001\u7cbe\u5ea6\u3001\u7528\u6237\u4f53\u9a8c\uff0c\u540c\u65f6\u4e5f\u7f13\u89e3\u4e86\u533b\u7597\u8d44\u6e90\u7684\u538b\u529b\u548c\u7cbe\u786e\u5ea6\u4e0d\u591f\u7684\u95ee\u9898\u3002<\/p>\n
\n01\u533b\u5b66\u6570\u636e\u96c6<\/p>\n<\/blockquote>\n
\u667a\u80fd\u533b\u7597\u6709\u5f88\u591a\u7684\u53d1\u5c55\u65b9\u5411\uff0c\u4f8b\u5982\u533b\u5b66\u5f71\u50cf\u5904\u7406\u3001\u8bca\u65ad\u9884\u6d4b\u3001\u75be\u75c5\u63a7\u5236\u3001\u5065\u5eb7\u7ba1\u7406\u3001\u5eb7\u590d\u673a\u5668\u4eba\u3001\u8bed\u97f3\u8bc6\u522b\u75c5\u5386\u7535\u5b50\u5316\u7b49\u3002\u5f53\u524d\u4eba\u5de5\u667a\u80fd\u6280\u672f\u65b0\u7684\u53d1\u529b\u70b9\u4e2d\u7684\u533b\u5b66\u56fe\u50cf\u5728\u75be\u75c5\u7684\u9884\u6d4b\u548c\u81ea\u52a8\u5316\u8bca\u65ad\u65b9\u9762\u6709\u975e\u5e38\u5927\u7684\u610f\u4e49\uff0c\u672c\u7bc7\u5373\u9488\u5bf9\u533b\u5b66\u5f71\u50cf\u4e2d\u7684\u75c5\u4f8b\u5206\u6790\uff0c\u964d\u566a\uff0c\u5206\u5272\uff0c\u68c0\u7d22\u7b49\u9886\u57df\u6765\u4ecb\u7ecd\u4e00\u4e9b\u5e38\u7528\u7684\u6570\u636e\u96c6\u3002<\/p>\n
1.1 \u75c5\u4f8b\u5206\u6790\u6570\u636e\u96c6<\/p>\n
1.1.1 ABIDE<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http:\/\/preprocessed-connectomes-project.org\/abide\/<\/p>\n
\u53d1\u5e03\u4e8e2013\u5e74\uff0c\u8fd9\u662f\u4e00\u4e2a\u5bf9\u81ea\u95ed\u75c7\u5185\u5728\u5927\u8111\u7ed3\u6784\u7684\u5927\u89c4\u6a21\u8bc4\u4f30\u6570\u636e\u96c6\uff0c\u5305\u62ec539\u540d\u60a3\u6709ASD\u548c573\u540d\u6b63\u5e38\u4e2a\u4f53\u7684\u529f\u80fdMRI\u56fe\u50cf\u3002<\/p>\n
1.1.2 OASIS<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1ahttp:\/\/www.oasis-brains.org\/<\/p>\n
OASIS\uff0c\u5168\u79f0\u4e3aOpen Access Series of Imaging Studies\uff0c\u5df2\u7ecf\u53d1\u5e03\u4e86\u7b2c3\u4ee3\u7248\u672c\uff0c\u7b2c\u4e00\u6b21\u53d1\u5e03\u4e8e2007\u5e74\uff0c\u662f\u4e00\u9879\u65e8\u5728\u4f7f\u79d1\u5b66\u754c\u514d\u8d39\u63d0\u4f9b\u5927\u8111\u6838\u78c1\u5171\u632f\u6570\u636e\u96c6\u7684\u9879\u76ee\u3002\u5b83\u6709\u4e24\u4e2a\u6570\u636e\u96c6\u53ef\u7528\uff0c\u4e0b\u9762\u662f\u7b2c1\u7248\u7684\u4e3b\u8981\u5185\u5bb9\u3002<\/p>\n
(1) \u6a2a\u622a\u9762\u6570\u636e\u96c6\uff1a\u5e74\u8f7b\uff0c\u4e2d\u8001\u5e74\uff0c\u975e\u75f4\u5446\u548c\u75f4\u5446\u8001\u5e74\u4eba\u7684\u6a2a\u65ad\u9762MRI\u6570\u636e\u3002\u8be5\u7ec4\u7531416\u540d\u5e74\u9f84\u572818\u5c81\u81f396\u5c81\u7684\u53d7\u8bd5\u8005\u7ec4\u6210\u7684\u6a2a\u622a\u9762\u6570\u636e\u5e93\u7ec4\u6210\u3002\u5bf9\u4e8e\u6bcf\u4f4d\u53d7\u8bd5\u8005\uff0c\u5355\u72ec\u83b7\u5f973\u62164\u4e2a\u5355\u72ec\u7684T1\u52a0\u6743MRI\u626b\u63cf\u5305\u62ec\u626b\u63cf\u4f1a\u8bdd\u3002\u53d7\u8bd5\u8005\u90fd\u662f\u53f3\u6487\u5b50\uff0c\u5305\u62ec\u7537\u6027\u548c\u5973\u6027\u3002100\u540d60\u5c81\u4ee5\u4e0a\u7684\u53d7\u8bd5\u8005\u5df2\u7ecf\u4e34\u5e8a\u8bca\u65ad\u4e3a\u8f7b\u5ea6\u81f3\u4e2d\u5ea6\u963f\u5c14\u8328\u6d77\u9ed8\u75c5\u3002<\/p>\n
(2) \u7eb5\u5411\u96c6\u6570\u636e\u96c6\uff1a\u975e\u75f4\u5446\u548c\u75f4\u5446\u8001\u5e74\u4eba\u7684\u7eb5\u5411\u78c1\u5171\u632f\u6210\u50cf\u6570\u636e\u3002\u8be5\u96c6\u5408\u5305\u62ec150\u540d\u5e74\u9f84\u572860\u81f396\u5c81\u7684\u53d7\u8bd5\u8005\u7684\u7eb5\u5411\u96c6\u5408\u3002\u6bcf\u4f4d\u53d7\u8bd5\u8005\u5728\u4e24\u6b21\u6216\u591a\u6b21\u8bbf\u89c6\u4e2d\u8fdb\u884c\u626b\u63cf\uff0c\u95f4\u9694\u81f3\u5c11\u4e00\u5e74\uff0c\u603b\u5171\u8fdb\u884c373\u6b21\u6210\u50cf\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u53d7\u8bd5\u8005\uff0c\u5305\u62ec\u5728\u5355\u6b21\u626b\u63cf\u671f\u95f4\u83b7\u5f97\u76843\u62164\u6b21\u5355\u72ec\u7684T1\u52a0\u6743MRI\u626b\u63cf\u3002\u53d7\u8bd5\u8005\u90fd\u662f\u53f3\u6487\u5b50\uff0c\u5305\u62ec\u7537\u6027\u548c\u5973\u6027\u3002\u5728\u6574\u4e2a\u7814\u7a76\u4e2d\uff0c72\u540d\u53d7\u8bd5\u8005\u88ab\u63cf\u8ff0\u4e3a\u672a\u88ab\u8bc1\u5b9e\u3002\u5305\u62ec\u7684\u53d7\u8bd5\u8005\u4e2d\u670964\u4eba\u5728\u521d\u6b21\u5c31\u8bca\u65f6\u8868\u73b0\u4e3a\u75f4\u5446\u75c7\uff0c\u5e76\u5728\u968f\u540e\u7684\u626b\u63cf\u4e2d\u4ecd\u7136\u5982\u6b64\uff0c\u5176\u4e2d\u5305\u62ec51\u540d\u8f7b\u5ea6\u81f3\u4e2d\u5ea6\u963f\u5c14\u8328\u6d77\u9ed8\u75c5\u60a3\u8005\u3002\u53e6\u591614\u540d\u53d7\u8bd5\u8005\u5728\u521d\u6b21\u5c31\u8bca\u65f6\u8868\u73b0\u4e3a\u672a\u8870\u9000\uff0c\u968f\u540e\u5728\u968f\u540e\u7684\u8bbf\u89c6\u4e2d\u8868\u73b0\u4e3a\u75f4\u5446\u75c7\u3002<\/p>\n
1.1.3 DDSM<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http:\/\/marathon.csee.usf.edu\/Mammography\/Database.html<\/p>\n
\u53d1\u5e03\u4e8e2000\u5e74\uff0c\u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u7b5b\u9009\u4e73\u817a\u6444\u5f71\u7684\u6570\u5b57\u6570\u636e\u5e93\uff0c\u662f\u4e73\u817a\u6444\u5f71\u56fe\u50cf\u5206\u6790\u7814\u7a76\u793e\u533a\u4f7f\u7528\u7684\u8d44\u6e90\u3002\u8be5\u9879\u76ee\u7684\u4e3b\u8981\u652f\u6301\u6765\u81ea\u7f8e\u56fd\u9646\u519b\u533b\u5b66\u7814\u7a76\u548c\u88c5\u5907\u53f8\u4ee4\u90e8\u7684\u4e73\u817a\u764c\u7814\u7a76\u8ba1\u5212\u3002DDSM\u9879\u76ee\u662f\u7531\u9a6c\u8428\u8bf8\u585e\u5dde\u7efc\u5408\u533b\u9662\uff08D. Kopans\uff0cR. Moore\uff09\uff0c\u5357\u4f5b\u7f57\u91cc\u8fbe\u5927\u5b66\uff08K.Bowyer\uff09\u548c\u6851\u8fea\u4e9a\u56fd\u5bb6\u5b9e\u9a8c\u5ba4\uff08P. Kegelmeyer\uff09\u5171\u540c\u53c2\u4e0e\u7684\u5408\u4f5c\u9879\u76ee\u3002\u6570\u636e\u5e93\u7684\u4e3b\u8981\u76ee\u7684\u662f\u4fc3\u8fdb\u8ba1\u7b97\u673a\u7b97\u6cd5\u5f00\u53d1\u65b9\u9762\u7684\u826f\u597d\u7814\u7a76\uff0c\u4ee5\u5e2e\u52a9\u7b5b\u9009\u3002\u6570\u636e\u5e93\u7684\u6b21\u8981\u76ee\u7684\u53ef\u80fd\u5305\u62ec\u5f00\u53d1\u7b97\u6cd5\u4ee5\u5e2e\u52a9\u8bca\u65ad\u548c\u5f00\u53d1\u6559\u5b66\u6216\u57f9\u8bad\u8f85\u52a9\u5de5\u5177\u3002\u8be5\u6570\u636e\u5e93\u5305\u542b\u7ea62,500\u9879\u7814\u7a76\u3002\u6bcf\u9879\u7814\u7a76\u5305\u62ec\u6bcf\u4e2a\u4e73\u623f\u7684\u4e24\u5e45\u56fe\u50cf\uff0c\u4ee5\u53ca\u4e00\u4e9b\u76f8\u5173\u7684\u60a3\u8005\u4fe1\u606f\uff08\u7814\u7a76\u65f6\u95f4\uff0cACR\u4e73\u623f\u5bc6\u5ea6\u8bc4\u5206\uff0c\u5f02\u5e38\u5fae\u5999\u8bc4\u7ea7\uff0c\u5f02\u5e38ACR\u5173\u952e\u5b57\u63cf\u8ff0\uff09\u548c\u56fe\u50cf\u4fe1\u606f\uff08\u626b\u63cf\u4eea\uff0c\u7a7a\u95f4\u5206\u8fa8\u7387\u7b49\uff09\u3002\u5305\u542b\u53ef\u7591\u533a\u57df\u7684\u56fe\u50cf\u5177\u6709\u5173\u4e8e\u53ef\u7591\u533a\u57df\u7684\u4f4d\u7f6e\u548c\u7c7b\u578b\u7684\u50cf\u7d20\u7ea7\u201c\u5730\u9762\u771f\u5b9e\u201d\u4fe1\u606f\u3002<\/p>\n
1.1.4 MIAS<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http:\/\/peipa.essex.ac.uk\/pix\/mias\/all-mias.tar.gz<\/p>\n
https:\/\/www.repository.cam.ac.uk\/handle\/1810\/250394?show=full<\/p>\n
MIAS\u5168\u79f0\u4e3aMiniMammographic Database\uff0c\u662f\u4e73\u817a\u56fe\u50cf\u6570\u636e\u5e93\u3002<\/p>\n
<\/p>\n
\u4e73\u817aMG\u6570\u636e\uff08Breast Mammography\uff09\u6709\u4e2a\u4e13\u95e8\u7684database\uff0c\u53ef\u4ee5\u67e5\u770b\u5f88\u591a\u6570\u636e\u96c6\uff0c\u94fe\u63a5\u5730\u5740\u4e3a\uff1a<\/p>\n
http:\/\/www.mammoimage.org\/databases\/<\/p>\n
1.1.5 MURA<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
https:\/\/stanfordmlgroup.github.io\/competitions\/mura\/<\/p>\n
\u53d1\u5e03\u4e8e2018\u5e742\u6708\uff0c\u5434\u6069\u8fbe\u56e2\u961f\u5f00\u6e90\u4e86 MURA \u6570\u636e\u5e93\uff0cMURA \u662f\u76ee\u524d\u6700\u5927\u7684 X \u5149\u7247\u6570\u636e\u5e93\u4e4b\u4e00\u3002\u8be5\u6570\u636e\u5e93\u4e2d\u5305\u542b\u4e86\u6e90\u81ea14982\u9879\u75c5\u4f8b\u768440895\u5f20\u808c\u8089\u9aa8\u9abcX\u5149\u7247\u30021\u4e07\u591a\u9879\u75c5\u4f8b\u91cc\u67099067\u4f8b\u6b63\u5e38\u7684\u4e0a\u7ea7\u808c\u8089\u9aa8\u9abc\u548c5915\u4f8b\u4e0a\u80a2\u5f02\u5e38\u808c\u8089\u9aa8\u9abc\u7684X\u5149\u7247\uff0c\u90e8\u4f4d\u5305\u62ec\u80a9\u90e8\u3001\u80b1\u9aa8\u3001\u624b\u8098\u3001\u524d\u81c2\u3001\u624b\u8155\u3001\u624b\u638c\u548c\u624b\u6307\u3002\u6bcf\u4e2a\u75c5\u4f8b\u5305\u542b\u4e00\u4e2a\u6216\u591a\u4e2a\u56fe\u50cf\uff0c\u5747\u7531\u653e\u5c04\u79d1\u533b\u5e08\u624b\u52a8\u6807\u8bb0\u3002\u5168\u7403\u6709\u8d85\u8fc717\u4ebf\u4eba\u90fd\u6709\u808c\u8089\u9aa8\u9abc\u6027\u7684\u75be\u75c5\uff0c\u56e0\u6b64\u8bad\u7ec3\u8fd9\u4e2a\u6570\u636e\u96c6\uff0c\u5e76\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u68c0\u6d4b\u9aa8\u9abc\u75be\u75c5\uff0c\u8fdb\u884c\u81ea\u52a8\u5f02\u5e38\u5b9a\u4f4d\uff0c\u901a\u8fc7\u7ec4\u7ec7\u5668\u5b98\u7684X\u5149\u7247\u6765\u786e\u5b9a\u673a\u4f53\u7684\u5065\u5eb7\u72b6\u51b5\uff0c\u8fdb\u800c\u5bf9\u60a3\u8005\u7684\u75c5\u60c5\u8fdb\u884c\u8bca\u65ad\uff0c\u53ef\u4ee5\u5e2e\u52a9\u7f13\u89e3\u653e\u5c04\u79d1\u533b\u751f\u7684\u75b2\u52b3\u3002<\/p>\n
\u516c\u5f00\u53ef\u7528\u7684\u533b\u5b66\u5c04\u7ebf\u7167\u76f8\u56fe\u50cf\u6570\u636e\u96c6\u6982\u8ff0<\/p>\n
<\/p>\n
<\/p>\n
\u53c2\u80032018\u5e74\u8bba\u6587\uff1aMURA: Large Dataset for Abnormality Detection inMusculoskeletal Radiographs.<\/p>\n
1.1.6 ChestX-ray14<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
https:\/\/www.kaggle.com\/nih-chest-xrays\/data<\/p>\n
https:\/\/nihcc.app.box.com\/v\/ChestXray-NIHCC<\/p>\n
\u53c2\u8003\u8bba\u6587\uff1a<\/p>\n
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with DeepLearning<\/p>\n
ChestX-ray14 \u662f\u7531NIH\u7814\u7a76\u9662\u63d0\u4f9b\u7684\uff0c\u5176\u4e2d\u5305\u542b\u4e8630,805\u540d\u60a3\u8005\u7684112,120\u4e2a\u5355\u72ec\u6807\u6ce8\u768414\u79cd\u4e0d\u540c\u80ba\u90e8\u75be\u75c5\uff08\u80ba\u4e0d\u5f20\u3001\u53d8\u5b9e\u3001\u6d78\u6da6\u3001\u6c14\u80f8\u3001\u6c34\u80bf\u3001\u80ba\u6c14\u80bf\u3001\u7ea4\u7ef4\u53d8\u6027\u3001\u79ef\u6db2\u3001\u80ba\u708e\u3001\u80f8\u819c\u589e\u539a\u3001\u5fc3\u810f\u80a5\u5927\u3001\u7ed3\u8282\u3001\u80bf\u5757\u548c\u759d\u6c14\uff09\u7684\u6b63\u9762\u80f8\u90e8 X \u5149\u7247\u3002\u7814\u7a76\u4eba\u5458\u5bf9\u6570\u636e\u91c7\u7528NLP\u65b9\u6cd5\u5bf9\u56fe\u50cf\u8fdb\u884c\u6807\u6ce8\u3002\u5229\u7528\u6df1\u5ea6\u5b66\u4e60\u7684\u6280\u672f\u65e9\u671f\u53d1\u73b0\u5e76\u8bc6\u522b\u80f8\u900f\u7167\u7247\u4e2d\u80ba\u708e\u7b49\u75be\u75c5\u5bf9\u589e\u52a0\u60a3\u8005\u6062\u590d\u548c\u751f\u5b58\u7684\u6700\u4f73\u673a\u4f1a\u81f3\u5173\u91cd\u8981\u3002<\/p>\n
1.1.7 LIDC-IDRI<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
https:\/\/wiki.cancerimagingarchive.net\/display\/Public\/LIDC-IDRI<\/p>\n
LIDC-IDRI\u6570\u636e\u96c6\u662f\u7531\u7f8e\u56fd\u56fd\u5bb6\u764c\u75c7\u7814\u7a76\u6240(National Cancer Institute)\u53d1\u8d77\u6536\u96c6\u7684\uff0c\u76ee\u7684\u662f\u4e3a\u4e86\u7814\u7a76\u9ad8\u5371\u4eba\u7fa4\u65e9\u671f\u80ba\u7ed3\u8282\u68c0\u6d4b\u3002\u8be5\u6570\u636e\u96c6\u4e2d\uff0c\u5171\u6536\u5f55\u4e861018\u4e2a\u7814\u7a76\u5b9e\u4f8b\u3002\u5bf9\u4e8e\u6bcf\u4e2a\u5b9e\u4f8b\u4e2d\u7684\u56fe\u50cf\uff0c\u90fd\u75314\u4f4d\u7ecf\u9a8c\u4e30\u5bcc\u7684\u80f8\u90e8\u653e\u5c04\u79d1\u533b\u5e08\u8fdb\u884c\u4e24\u9636\u6bb5\u7684\u8bca\u65ad\u6807\u6ce8\u3002\u8be5\u6570\u636e\u96c6\u7531\u80f8\u90e8\u533b\u5b66\u56fe\u50cf\u6587\u4ef6(\u5982CT\u3001X\u5149\u7247)\u548c\u5bf9\u5e94\u7684\u8bca\u65ad\u7ed3\u679c\u75c5\u53d8\u6807\u6ce8\u7ec4\u6210\u3002<\/p>\n
1.1.8 LUNA16<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
https:\/\/luna16.grand-challenge.org\/Home\/<\/p>\n
\u53d1\u5e03\u4e8e2016\u5e74\uff0c\u662f\u80ba\u90e8\u80bf\u7624\u68c0\u6d4b\u6700\u5e38\u7528\u7684\u6570\u636e\u96c6\u4e4b\u4e00\uff0c\u5b83\u5305\u542b888\u4e2aCT\u56fe\u50cf\uff0c1084\u4e2a\u80bf\u7624\uff0c\u56fe\u50cf\u8d28\u91cf\u548c\u80bf\u7624\u5927\u5c0f\u7684\u8303\u56f4\u6bd4\u8f83\u7406\u60f3\u3002\u6570\u636e\u5206\u4e3a10\u4e2asubsets\uff0csubset\u5305\u542b89\/88\u4e2aCT scan\u3002<\/p>\n
LUNA16\u7684CT\u56fe\u50cf\u53d6\u81eaLIDC\/IDRI\u6570\u636e\u96c6\uff0c\u9009\u53d6\u4e86\u4e09\u4e2a\u4ee5\u4e0a\u653e\u5c04\u79d1\u533b\u5e08\u610f\u89c1\u4e00\u81f4\u7684annotation\uff0c\u5e76\u4e14\u53bb\u6389\u4e86\u5c0f\u4e8e3mm\u7684\u80bf\u7624\uff0c\u6240\u4ee5\u6570\u636e\u96c6\u91cc\u4e0d\u542b\u6709\u5c0f\u4e8e3mm\u7684\u80bf\u7624\uff0c\u4fbf\u4e8e\u8bad\u7ec3\u3002<\/p>\n
1.1.9 NSCLC<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
https:\/\/wiki.cancerimagingarchive.net\/display\/Public\/NSCLC+Radiogenomics<\/p>\n
\u53d1\u5e03\u4e8e2018\u5e74\uff0c\u6765\u81ea\u65af\u5766\u798f\u5927\u5b66\u3002\u6570\u636e\u96c6\u6765\u81ea211\u540d\u53d7\u8bd5\u8005\u7684\u975e\u5c0f\u7ec6\u80de\u80ba\u764c\uff08NSCLC\uff09\u961f\u5217\u7684\u72ec\u7279\u653e\u5c04\u57fa\u56e0\u7ec4\u6570\u636e\u96c6\u3002\u8be5\u6570\u636e\u96c6\u5305\u62ec\u8ba1\u7b97\u673a\u65ad\u5c42\u626b\u63cf\uff08CT\uff09\uff0c\u6b63\u7535\u5b50\u53d1\u5c04\u65ad\u5c42\u626b\u63cf\uff08PET\uff09\/ CT\u56fe\u50cf\u3002\u521b\u5efa\u8be5\u6570\u636e\u96c6\u662f\u4e3a\u4e86\u4fbf\u4e8e\u53d1\u73b0\u57fa\u56e0\u7ec4\u548c\u533b\u5b66\u56fe\u50cf\u7279\u5f81\u4e4b\u95f4\u7684\u57fa\u7840\u5173\u7cfb\uff0c\u4ee5\u53ca\u9884\u6d4b\u533b\u5b66\u56fe\u50cf\u751f\u7269\u6807\u8bb0\u7684\u5f00\u53d1\u548c\u8bc4\u4f30\u3002<\/p>\n
1.1.10 DeepLesion<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
https:\/\/nihcc.app.box.com\/v\/DeepLesion<\/p>\n
DeepLesion\u7531\u7f8e\u56fd\u56fd\u7acb\u536b\u751f\u7814\u7a76\u9662\u4e34\u5e8a\u4e2d\u5fc3\uff08NIHCC\uff09\u7684\u56e2\u961f\u5f00\u53d1\uff0c\u662f\u8fc4\u4eca\u89c4\u6a21\u6700\u5927\u7684\u591a\u7c7b\u522b\u3001\u75c5\u7076\u7ea7\u522b\u6807\u6ce8\u4e34\u5e8a\u533b\u7597CT\u56fe\u50cf\u5f00\u653e\u6570\u636e\u96c6\u3002\u5728\u8be5\u6570\u636e\u5e93\u4e2d\u56fe\u50cf\u5305\u62ec\u591a\u79cd\u75c5\u53d8\u7c7b\u578b\uff0c\u76ee\u524d\u5305\u62ec4427\u4e2a\u60a3\u8005\u768432,735 \u5f20CT\u56fe\u50cf\u53ca\u75c5\u53d8\u4fe1\u606f\uff0c\u540c\u65f6\u4e5f\u5305\u62ec\u80be\u810f\u75c5\u53d8\uff0c\u9aa8\u75c5\u53d8\uff0c\u80ba\u7ed3\u8282\u548c\u6dcb\u5df4\u7ed3\u80bf\u5927\u3002DeepLesion\u591a\u7c7b\u522b\u75c5\u53d8\u6570\u636e\u96c6\u53ef\u4ee5\u7528\u6765\u5f00\u53d1\u81ea\u52a8\u5316\u653e\u5c04\u8bca\u65ad\u7684CADx\u7cfb\u7edf\u3002<\/p>\n
1.1.11 ADNI<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http : \/\/adni.loni.usc.edu\/data-samples\/access-data\/<\/p>\n
ANDI\u6d89\u53ca\u5230\u7684\u6570\u636e\u96c6\u5305\u62ec\u5982\u4e0b\u51e0\u90e8\u5206Clinical Data\uff08\u4e34\u5e8a\u6570\u636e\uff09\u3001MR Image Data\uff08\u78c1\u5171\u632f\u6210\u50cf\uff09\u3001Standardized MRI Data Sets\u3001PET Image Data\uff08\u6b63\u7535\u5b50\u53d1\u5c04\u8ba1\u7b97\u673a\u65ad\u5c42\u626b\u63cf\uff09\u3001Gennetic Data\uff08\u9057\u4f20\u6570\u636e\uff09\u3001Biospecimen Data\uff08\u751f\u7269\u6837\u672c\u6570\u636e\uff09\u3002<\/p>\n
1.2 \u533b\u5b66\u964d\u566a\u6570\u636e\u96c6<\/p>\n
1.2.1 BrainWeb\u6570\u636e\u96c6<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http:\/\/brainweb.bic.mni.mcgill.ca\/brainweb\/<\/p>\n
\u53d1\u5e03\u4e8e1997\u5e74\uff0c\u8fd9\u662f\u4e00\u4e2a\u4eff\u771f\u6570\u636e\u96c6\uff0c\u7528\u4e8e\u533b\u5b66\u56fe\u50cf\u964d\u566a\u3002\u7814\u7a76\u8005\u53ef\u4ee5\u622a\u53d6\u4e0d\u540c\u65ad\u5c42\u7684\u6b63\u5e38\u8111\u90e8\u4eff\u771f\u56fe\u50cf\uff0c\u5305\u62ecT1\uff0cT2\uff0cPD3\u79cd\u65ad\u5c42\uff0c\u8bbe\u7f6e\u65ad\u5c42\u7684\u539a\u5ea6\uff0c\u53e0\u52a0\u9ad8\u65af\u566a\u58f0\u6216\u8005\u533b\u5b66\u56fe\u50cf\u4e2d\u5e38\u89c1\u7684\u83b1\u65af\u566a\u58f0\uff0c\u6700\u7ec8\u4f1a\u5f97\u5230181\u00d7217\u5927\u5c0f\u7684\u566a\u58f0\u56fe\u50cf\u3002<\/p>\n
1.3 \u533b\u5b66\u5206\u5272\u6570\u636e\u96c6<\/p>\n
1.3.1 DRIVE\u6570\u636e\u96c6<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http:\/\/www.isi.uu.nl\/Research\/Databases\/DRIVE\/download.php<\/p>\n
\u53d1\u5e03\u4e8e2003\u5e74\uff0c\u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u8840\u7ba1\u5206\u5272\u7684\u6570\u5b57\u89c6\u7f51\u819c\u56fe\u50cf\u6570\u636e\u96c6\uff0c\u5b83\u753140\u5f20\u7167\u7247\u7ec4\u6210\uff0c\u5176\u4e2d7\u5f20\u663e\u793a\u51fa\u8f7b\u5ea6\u65e9\u671f\u7cd6\u5c3f\u75c5\u89c6\u7f51\u819c\u75c5\u53d8\u8ff9\u8c61\u3002<\/p>\n
1.3.2 SCR\u6570\u636e\u96c6<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http:\/\/www.isi.uu.nl\/Research\/Databases\/SCR\/<\/p>\n
\u53d1\u5e03\u4e8e2000\u5e74\uff0c\u80f8\u90e8X\u5149\u7247\u7684\u5206\u5272\uff0c\u80f8\u90e8X\u5149\u7247\u4e2d\u89e3\u5256\u7ed3\u6784\u7684\u81ea\u52a8\u5206\u5272\u5bf9\u4e8e\u8fd9\u4e9b\u56fe\u50cf\u4e2d\u7684\u8ba1\u7b97\u673a\u8f85\u52a9\u8bca\u65ad\u975e\u5e38\u91cd\u8981\u3002SCR\u6570\u636e\u5e93\u7684\u5efa\u7acb\u662f\u4e3a\u4e86\u4fbf\u4e8e\u6bd4\u8f83\u7814\u7a76\u80ba\u91ce\uff0c\u5fc3\u810f\u548c\u9501\u9aa8\u5728\u6807\u51c6\u7684\u540e\u80f8\u524dX\u7ebf\u7247\u4e0a\u7684\u5206\u5272\u3002<\/p>\n
<\/p>\n
\u672c\u7740\u5408\u4f5c\u79d1\u5b66\u8fdb\u6b65\u7684\u7cbe\u795e\uff0c\u6211\u4eec\u53ef\u4ee5\u81ea\u7531\u5171\u4eabSCR\u6570\u636e\u5e93\uff0c\u5e76\u81f4\u529b\u4e8e\u5728\u8fd9\u4e9b\u5206\u5272\u4efb\u52a1\u4e0a\u7ef4\u62a4\u5404\u79cd\u7b97\u6cd5\u7ed3\u679c\u7684\u516c\u5171\u5b58\u50a8\u5e93\u3002\u5728\u8fd9\u4e9b\u9875\u9762\u4e0a\uff0c\u53ef\u4ee5\u5728\u4e0b\u8f7d\u6570\u636e\u5e93\u548c\u4e0a\u8f7d\u7ed3\u679c\u65f6\u627e\u5230\u8bf4\u660e\uff0c\u5e76\u4e14\u53ef\u4ee5\u68c0\u67e5\u5404\u79cd\u65b9\u6cd5\u7684\u57fa\u51c6\u7ed3\u679c\u3002<\/p>\n
1.3.3 \u533b\u5b66\u56fe\u50cf\u5206\u6790benchmark<\/p>\n
\u5728\u7f51\u5740https:\/\/grand-challenge.org\/challenges\/\u63d0\u4f9b\u4e86\u65f6\u95f4\u8de8\u5ea6\u8d85\u8fc710\u5e74\u7684\u533b\u5b66\u56fe\u50cf\u8d44\u6599\u3002<\/p>\n
1.3.4 Ardiac MRI<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
http:\/\/www.cse.yorku.ca\/~mridataset\/<\/p>\n
ardiac MRI \u662f\u5fc3\u810f\u75c5\u60a3\u8005\u5fc3\u623f\u533b\u7597\u5f71\u50cf\u6570\u636e\uff0c\u4ee5\u53ca\u5176\u5de6\u5fc3\u5ba4\u7684\u5fc3\u5185\u819c\u548c\u5916\u819c\u7684\u56fe\u50cf\u6807\u6ce8\u3002\u5305\u62ec33\u4f4d\u60a3\u8005\u6848\u4f8b\uff0c\u6bcf\u4e2a\u53d7\u8bd5\u8005\u7684\u5e8f\u5217\u7531\u6cbf\u7740\u957f\u768420\u5e27\u548c8-15\u4e2a\u5207\u7247\u7ec4\u6210\uff0c\u51717980\u5f20\u56fe\u50cf\u3002<\/p>\n
1.3.5 NIH<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
https:\/\/www.kaggle.com\/nih-chest-xrays<\/p>\n
\u53d1\u5e03\u4e8e2017\u5e74\uff0c\u8fd9\u662f\u4e00\u4e2a\u80f8\u90e8X\u5c04\u7ebf\u6570\u636e\u96c6\uff0c\u5305\u542b30,805\u4e2a\u60a3\u8005\uff0c14\u4e2a\u75be\u75c5\u56fe\u50cf\u6807\u7b7e\uff08\u5176\u4e2d\u6bcf\u4e2a\u56fe\u50cf\u53ef\u4ee5\u5177\u6709\u591a\u4e2a\u6807\u7b7e\uff09\uff0c112,820\u4e2a\u6b63\u9762X\u5c04\u7ebf\u56fe\u50cf\uff0c\u6807\u7b7e\u662f\u4f7f\u7528\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4ece\u76f8\u5173\u7684\u653e\u5c04\u5b66\u62a5\u544a\u4e2d\u81ea\u52a8\u63d0\u53d6\u3002\u5341\u56db\u79cd\u5e38\u89c1\u7684\u80f8\u90e8\u75c5\u53d8\u5305\u62ec\u80ba\u4e0d\u5f20\uff0c\u5de9\u56fa\uff0c\u6d78\u6da6\uff0c\u6c14\u80f8\uff0c\u6c34\u80bf\uff0c\u80ba\u6c14\u80bf\uff0c\u7ea4\u7ef4\u5316\uff0c\u79ef\u6db2\uff0c\u80ba\u708e\uff0c\u80f8\u819c\u589e\u539a\uff0c\u5fc3\u810f\u6269\u5927\uff0c\u7ed3\u8282\uff0c\u80bf\u5757\u548c\u759d\u3002\u7531\u4e8e\u8bb8\u591a\u539f\u56e0\uff0c\u539f\u59cb\u653e\u5c04\u5b66\u62a5\u544a\uff08\u4e0e\u8fd9\u4e9b\u80f8\u90e8X\u5c04\u7ebf\u7814\u7a76\u76f8\u5173\uff09\u5e76\u4e0d\u662f\u516c\u5f00\u5206\u4eab\u7684\u3002\u6240\u4ee5\u6587\u672c\u6316\u6398\u7684\u75be\u75c5\u6807\u7b7e\u9884\u8ba1\u51c6\u786e\u5ea6 > 90\uff05\uff0c\u8fd9\u4e2a\u6570\u636e\u96c6\u9002\u5408\u505a\u534a\u76d1\u7763\u7684\u5b66\u4e60\u3002<\/p>\n
1.4 List of Open Access <\/p>\n
\u5728List of Open Access Medical Imaging Datasets\u7f51\u7ad9\u4e0a\u53ef\u4ee5\u770b\u5230\u66f4\u591a\u7684\u76f8\u5173\u65b9\u5411\u7684\u6570\u636e\u96c6\u3002<\/p>\n
\u6570\u636e\u96c6\u5730\u5740\uff1a<\/p>\n
List of Open Access Medical Imaging Datasets<\/p><\/blockquote>\n