{"id":607,"date":"2025-04-03T10:22:40","date_gmt":"2025-04-03T02:22:40","guid":{"rendered":"http:\/\/106.52.84.14\/?p=570"},"modified":"2025-04-03T10:22:40","modified_gmt":"2025-04-03T02:22:40","slug":"20-08-mics%e5%9c%a8%e7%ba%bf%e5%ad%a6%e6%9c%af%e8%ae%b2%e5%ba%a7%ef%bc%9a%e5%94%90%e6%99%93%e9%a2%96","status":"publish","type":"post","link":"https:\/\/www.mics-ai.com\/index.php\/2025\/04\/03\/20-08-mics%e5%9c%a8%e7%ba%bf%e5%ad%a6%e6%9c%af%e8%ae%b2%e5%ba%a7%ef%bc%9a%e5%94%90%e6%99%93%e9%a2%96\/","title":{"rendered":"[#20-08] MICS\u5728\u7ebf\u5b66\u672f\u8bb2\u5ea7\uff1a\u5510\u6653\u9896"},"content":{"rendered":"\n
\u5609\u5bbe<\/strong><\/td>\u5510\u6653\u9896\uff08\u5357\u65b9\u79d1\u6280\u5927\u5b66\uff09<\/td><\/tr>
\u65f6\u95f4<\/strong><\/td>2020\u5e746\u670816\u65e5\uff08\u661f\u671f\u4e8c\uff09\u665a\u4e0a20:00\uff08\u5317\u4eac\u65f6\u95f4\uff09<\/td><\/tr>
\u9898\u76ee<\/strong><\/td>Large deformation diffeomorphic metric mapping with applications in neuroimaging and computer vision\uff08\u9ad8\u5ea6\u5f62\u53d8\u5fae\u5206\u540c\u80da\u5ea6\u91cf\u6620\u5c04\u53ca\u5176\u5728\u795e\u7ecf\u5f71\u50cf\u548c\u8ba1\u7b97\u673a\u89c6\u89c9\u4e2d\u7684\u5e94\u7528\uff09<\/td><\/tr>
\u4e3b\u6301<\/strong><\/td>\u9648\u5b87\u98de\uff08\u540c\u6d4e\u5927\u5b66\uff09<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n
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\u62a5\u544a\u6458\u8981<\/strong><\/p>\n\n\n\n

Establishing correspondence between different coordinate systems is very important and of wide applications in various aspects of neuroimaging and computer vision. Among all types of coordinate transformations, diffeomorphisms are of superior property given that they can preserve topology so that connected sets stay connected. In this talk, I will first introduce an approach for building a diffeomorphic correspondence between two coordinate systems in the framework of large deformation diffeomorphic metric mapping. With this established, I will cover several applications in neuroimaging and computer vision. The first one will be about MRI based brain segmentation. The second application will be focused on statistical shape analysis of brain structures in the neuropathology of different brain disorders. At the end of this talk, I will introduce the utility of diffeomorphic mapping with respect to two classical computer vision problems, facial expression recognition and facial landmark detection. Results from various datasets will be presented.<\/p>\n\n\n\n

\u5609\u5bbe\u7b80\u4ecb<\/strong><\/p>\n\n\n\n

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\u7279\u522b\u611f\u8c22\u672c\u6b21Webinar\u4e3b\u8981\u7ec4\u7ec7\u8005\uff1a<\/strong><\/p>\n\n\n\n

\u9648\u5b87\u98de\uff08\u540c\u6d4e\u5927\u5b66\uff09<\/strong><\/p>\n\n\n\n

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  1. MICS\u5728\u7ebf\u5b66\u672f\u8bb2\u5ea7\u5df2\u8f6c\u6362\u5230Zoom\u5e73\u53f0\uff0c\u672c\u671f\u4f1a\u8baeID\uff1a94278447020\uff0c\u5bc6\u7801\uff1a123456\uff1b\u60a8\u53ef\u4ee5\u70b9\u51fb\u4ee5\u4e0b\u94fe\u63a5https:\/\/zoom.com.cn\/j\/94278447020\uff0c\u5e76\u6839\u636e\u9875\u9762\u63d0\u793a\u64cd\u4f5c\u8fdb\u5165\u4f1a\u8bae\uff1b\u8bf7\u6ce8\u610f\uff0c\u4f7f\u7528Zoom\u9700\u5b89\u88c5\u76f8\u5e94\u7684\u5ba2\u6237\u7aef\uff1b<\/li>\n\n\n\n
  2. \u60a8\u4e5f\u53ef\u4ee5\u901a\u8fc7Bilibili\u540c\u6b65\u89c2\u770b\u8f6c\u64ad\uff0c\u8bf7\u70b9\u51fb\u4ee5\u4e0b\u94fe\u63a5https:\/\/live.bilibili.com\/22188809\uff0c\u6216\u626b\u63cf\u4e8c\u7ef4\u7801\u8fdb\u5165\u8f6c\u64ad\uff1b
    \"\u56fe\u7247\"\u53ef\u76f4\u63a5\u626b\u63cf\u4e8c\u7ef4\u7801\u8fdb\u51656\u670816\u65e5B\u7ad9\u8f6c\u64ad<\/li>\n\n\n\n
  3. \u6d3b\u52a8\u5f00\u59cb\u524d5\u5206\u949f\u5de6\u53f3\uff0c\u4e3b\u6301\u4eba\u4f1a\u5f00\u542f\u76f4\u64ad\uff1b\u6b22\u8fce\u901a\u8fc7Zoom\u4e2d\u7684\u804a\u5929\u529f\u80fd\u4e0e\u8bb2\u8005\u3001\u4e3b\u6301\u4eba\u4e92\u52a8\uff0c\u63d0\u51fa\u95ee\u9898\uff1b<\/li>\n\n\n\n
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  5. \u540e\u7eed\u6bcf\u671f\u8bb2\u5ea7\u4fe1\u606f\uff0c\u4f1a\u901a\u8fc7MICS\u5fae\u4fe1\u516c\u4f17\u53f7\u201c\u533b\u5b66\u56fe\u50cf\u8ba1\u7b97\u9752\u5e74\u7814\u8ba8\u4f1a\u201d\uff08\u626b\u63cf\u4e0b\u65b9\u4e8c\u7ef4\u7801\u5173\u6ce8MICS\u5fae\u4fe1\u516c\u4f17\u53f7\uff09\u6216MICS QQ\u7fa4\uff08\u7fa4\u53f7\uff1a1067775650\uff09\u8fdb\u884c\u901a\u77e5\uff08\u6ce8\uff1a\u7533\u8bf7\u52a0\u5165MICS QQ\u7fa4\u65f6\u9700\u9a8c\u8bc1\u59d3\u540d\u3001\u5355\u4f4d\u548c\u8eab\u4efd\uff0c\u7f3a\u4e00\u4e0d\u53ef\uff1b\u5165\u7fa4\u540e\uff0c\u8bf7\u5b9e\u540d\uff0c\u59d3\u540d\u8eab\u4efd\u5355\u4f4d\uff1b\u8eab\u4efd\uff1a\u5b66\u6821\u53ca\u79d1\u7814\u5355\u4f4d\u4eba\u5458T\uff0c\u4f01\u4e1a\u7814\u53d1I\uff0c\u535a\u58ebD\uff0c\u7855\u58ebM\uff09\u3002<\/li>\n<\/ol>\n\n\n
    \n
    \"\"<\/figure>\n<\/div>\n\n\n

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    MICS\u5728\u7ebf\u5b66\u672f\u8bb2\u5ea7\u7684\u6a21\u5f0f\u548c\u7ec4\u7ec7\u65b9\u5f0f\u501f\u9274\u4e86\u5f88\u591aVALSE\u7684\u7ecf\u9a8c\uff0c\u4eceVALSE\u5f97\u5230\u4e86\u5f88\u591a\u7684\u542f\u53d1\uff0c\u5728\u6b64\u5bf9VALSE\u7ec4\u59d4\u4f1a\u8868\u793a\u8877\u5fc3\u7684\u611f\u8c22\uff0c\u4e5f\u795d\u613fMICS\u548cVALSE\u8d8a\u529e\u8d8a\u597d\uff01<\/p>\n","protected":false},"excerpt":{"rendered":"

    \u5609\u5bbe \u5510\u6653\u9896\uff08\u5357\u65b9\u79d1\u6280\u5927\u5b66\uff09 \u65f6\u95f4 20…<\/p>\n","protected":false},"author":1,"featured_media":576,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-607","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-6"],"_links":{"self":[{"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/posts\/607","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/comments?post=607"}],"version-history":[{"count":0,"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/posts\/607\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/media\/576"}],"wp:attachment":[{"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/media?parent=607"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/categories?post=607"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.mics-ai.com\/index.php\/wp-json\/wp\/v2\/tags?post=607"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}