[{"data":1,"prerenderedAt":46},["ShallowReactive",2],{"rendered-post-b1e8187e":3},{"abbrlink":4,"title":5,"date":6,"categories":7,"tags":9,"excerpt":11,"htmlChunkEnds":12,"toc":14,"htmlGzip":45},"b1e8187e","CT-Windowing医学CT图像增强","2022-10-06",[8],"图像处理",[10],"知识点","摘要 CT winding 是CT扫描的一项图像处理任务，它有助于突出关键的组织结构，通过修改 HU (Hounsfield Units) 参数，使图像更易于分析。",[13],8085,[15,19,22,26,30,33,37,41],{"id":16,"text":17,"html":17,"level":18},"post-heading-摘要","摘要",2,{"id":20,"text":21,"html":21,"level":18},"post-heading-hounsfield-unit-hu","Hounsfield Unit (HU)",{"id":23,"text":24,"html":25,"level":18},"post-heading-window-width-window-level","Window Width & Window Level","Window Width &amp; Window Level",{"id":27,"text":28,"html":28,"level":29},"post-heading-window-width-ww","Window Width (WW)",3,{"id":31,"text":32,"html":32,"level":29},"post-heading-window-level-wl","Window Level (WL)",{"id":34,"text":35,"html":36,"level":29},"post-heading-ww-wl-计算","WW & WL 计算","WW &amp; WL 计算",{"id":38,"text":39,"html":40,"level":29},"post-heading-ww-wl-示例","WW & WL 示例","WW &amp; WL 示例",{"id":42,"text":43,"html":44,"level":29},"post-heading-ww-wl-选择","WW & WL 选择","WW &amp; WL 选择","H4sIAAAAAAAAA+1ZW1MbRxZ+51d0zdamILEQErbBWJqHdW3i1OLsg\u002FFqq5IUNUgDmng0o8y0EGRrq8RdAoEgwTYIfCHBmOBCEg7BQheoyg\u002FYP+HpmdGT\u002FsJWT2tGGpAweFO1L\u002FGDpL6c09855zunT2NP0A24gJcKizJ0BFkmwAkjDnVlTd+ZoGjy7XEG3XSbJ0zfGQBRTsA7gLqWvTOgJl6rqZSWnlbyscrWMdo4QVMptD2tLc8qxSKa36qWkigzpW4m0PzPSmFJ25tAcwU080tlNaOlp7XitFac04o\u002FqM+mq6VkJZbWT+eU04y6egzuPgDtd8WIIA9zLB8ADwQOyh0ApSbVR7lqKamUT8lp6sahuvaDUlhC8Vn12fK72KTHGabbPFxoBMiS30s5uRAzwjrvDDh8nBAQo5wwgpJFtL9zZ6CG98dnqFRwdnVG2aEwBWQ4zrNe6jtRDPXd6PrzbQo46TZPMycFLXiOiMBBRzBC0Wcgg\u002Fa7Dzos9ymFXTWXqsyl9K3dainesFf2MzxbLSUqa0WUm9aW5rT0tPooV5lLoVwBFXbQ4iOlvIi9uVJGy4v63N4\u002F8b7Cqbb6qz69oj7eRweTVjRQakVdW1IKhcrrNVR6Utl4+9tb\u002FWBPfZzVD49RbhWdvK2W4p+JgWGJHQdfsNEhkQ+AOpxqKfEuNknQkpNRPq+t7iqFpZbHYmwbL9T9bZSKa69ySr5wZwDFStVS\u002FM4AECKhIVYiakl4wvTdBwDFSkp+qcYCgw5qfBl9n1Rjr\u002FTDXcyamV8svUrxJ31rFy1Pa68WLRGUnUWFnWopSbTpR\u002FOV12vVUlJ9uqw+XteP5vW5Q5SdxUpSi8rxglLY0aaPGlAoxZdKfkHJF7BiQyva3MXkI1FS8vOE3UphA8VKH0gtVxNq9V5IraihzxHlAjBoDnh2lOUpmhwFfHgJfMSEwrdBbaofb6iRLdj9PqXRM6rafT7M1G7DLepaFtwZADUrkjNo+bWWngY1Lyen0MYh9n5hpzKHI68Ui0r5kVJeUgpLwOcDSn6hsr6MYqW6EMrNos1dwhUlv6+unWjbBSVfqBRX9MSbaimpx5KV12uWgvkmCiwhbb2sJ940hLGSTmlPY1gSw\u002FrxGZp\u002FgWOem61sxvSdCXXjEG2\u002FsviCUmso+Vh9+lJdPUapNcIs9fmykt8zDjMojwk5kdMTbyprh6h88C42qZ+uK6U0ypYMUh2r2VVU2FEXn6PtA8JSbA4BQiA3YjEgpA2W43KHcrPa5oL+61v16UttI6+UcKagXFnLbKGZt+pmQskvouVkA8UTLc3FRQJHQT+ZQrnUGSux3w3E9XgSUld+3NQTb1BqRVt9TrZiI2rGYXl16aV+utKIGMVnKzOLWnHdAqdN5Ej+6afreINhreWbDy\u002FG3U0yBtzssVKmNbuNLHFE64liZAVo9\u002FXX2a1v7WrbBW3vCUr9pOT30emUGn+s5Pe1yeM63zCt8wWCSs+caGV8YwFfP9CP5pXyEg7po0Mlv1fDnZvFTjx5glcLmSax6sexqqwvEln9ZEopLzWy+0CfKmNWGEWIILSYXnfwzISeyde5ZKySe9NIwyU9ZrsaCRRSQKulpK8foPIB+mGRbMClrZD5nwJ1vUmg3hOnqCPKO\u002FTMlpZ5QtE+n1nD+gGZs6JEuEUqQbWU9vWDT3CRAk7g7mgzFxesRYe1+IGmuC+u0i1NwYE6WbCbQuYsU\u002FCdYqWf+vwlTv1yVikeKfl90vigfB7fd8btpr6YQ3OzWA36Pgl8Pis6kBniWfyNAeBvyRjQA5wsR1iPEwbJ2Odr+N1f++00djst2SExMG7pCNCVvV20fehxwgAZu7u6uuqjG9aAqDGl9MlCfZPrZqOI42YrmZnj+q7rjSLXWwhMr9T39DTs726xv5wlWdSw84bNmBa2PLXZUh\u002FcbC6gFX6tpFf12c1qKa5P5fWZ1Wop0cxnrc9U8vuVn5aqpbhSXiJVF7dV8WU0lbLp6r6E1VsxLbNFZBuhN0i6euyiTpMETpNZrVleiSXUhZ\u002FtLAdk0qK5ko+9i02oL47VxYyaiFU2Y5WpXXKVWkU1jrLHSmHJzD09ltR3Y9VSAsVnUX6KtBaVWAKl8HWkL7xU17IkP3ECaelpPfu0pksppY170ujN3mZQ\u002FLXR5mWV4kv91STKPtc2DtXH+FGCNc3toUxaOU7gS9NIq36SUwFuFPh5Rpa9lF8MsI4hXvQ\u002FpECAgYyjPkGf2wdFkR9iJIr2yGFGsC3xjDASYUZYig6Pw6AoeJx4C+0ZikAoCgCOh1kvRQaUTdAvhseto8PjxvmAkTjGwTNDLO+l0PYiih8pxZ+0FxMUgBzEhco2SXvk0REwyrHRv4hjXqoLdAH3deC+TgGj7fNSrpsUCLLcSBCS34b6IBcIsIKXglKEpcCw6I\u002FImBBeapjhZTzD8byXEkSBxeVREh+yXsofkSRWgHdEXpTMWYd5SGevNcVzAutnwl5KEiNCwDb9jcgJ5jztkVg\u002FBGNeqpcC48anqay7AXE3BaQxL+WmnLQnzMAgCHipe66boPcfNxg3cANscJfD7XDftY2Be\u002FRWfQzcwB3sxiqc8ugI7XGSYNAeZ4AbPR9q7M2wKEHq\u002FBK2wkFeN3IzXxJ20C6TAsan2zbqto2u20Y3bKObtlGPbdRrG92yjVxd9qEdjcuCQ6wPS6xpYpD\u002FRqYAZIY4IcBiNlE2NhLK4eQ6msHP+kwZd41PjlAqq+7uoeUVtZhG87sU7cG+sicKVu14yI5HRSlA0QF2uAYCnN9l0BwMRwQ\u002F5ERhkKKhxAjysCiFBv0QJ0tNtP28aJiRmJBM0TLLD18DpEM0XjvmwGgOrwFBlEIM7z2vgOcgKzE8RX+KE8FylPHV0dcGav\u002FOC8pQ4oQRiv7o24gIbzd+WkLqL7vqdIq0driPnCurj3JaehqD7TR6FiUfQ5k0OnmirmWHeZGB2kERPVvQ0vivJWh5B8XXUe5AffJCfRSvliYszRILI5LQB6AU8TOQDQBDG2D8flEy\u002FngDxZr9wGiXASMEzAkj6SxN5+HXjLd2hDih1mh7m7hhKMLxcJATKNrAb0aqwfkdwNFEjqQURXd1minw8RWVG2HusGAKbBQ3hF7QhCWjmNRDPAvMwj1IGFNTSGIBHHVTO4DzqrY2hfNlDdVHPLx9kRNqqr5u6uKzu1qdMXLhGa5LneE6e8YFOc1dkNLWJkE0\u002FVTLwXpO2aNW+\u002FXxBeDcN0yudHQyMr5lm8Tayss\u002Fjbl7bkc4AfaSn6boZUwj+WUBN6C1eZykyjnDEmvWUuOT\u002FOUvaXVG1ttLKz7XM1vK6ZY6kcWvt5MFtDNZe5I8ncMdTnkTPwEb3qnVUtLDfmsvpQ8ZyI5RTeYcIQYGQzxFe\u002FAPMBbiBWwKhOE+pzMajXZGuztFacTpunWr13mPgUHj414\u002F1sWGGAFyfpn2hCQxSntCIv3bgccZEmlPiKP\u002Fc+hxhjja4ySLjCCIkMHVGbCCX8Qlxksx4TDP+Y1Z55jDgPhVOAS+CrA8Ltl1GVxP68c5MVa68Yay2xSEIb71TWvuHWLks1MylCLQet2RhqKvq7Onp6eXDd0eZSXI+RnewfDciNDn6Ors6u3uZkO3qaZYQgYPsEearwFsBWG0dWSIkUY4wSHVDu7q7rll6MfObLxXzn6x39K48cWt7NsMoQTAL7w\u002Futc\u002Futc\u002Fulc7HJcdj8sOyGVH5LJDctkxueygXHZUbjsq9xkf2VG57ajcdlRuOyq3HZXbjsptR+W2UP3\u002FmncuhOll3ob3uVCYZz8f+NtFFygjm9tlDj5su7RyKEr+4Cgn45vmUurhaNtF2o3J9708jJlBir6PryvZuCW+MCo7951xf7V+fjTKA04IshIH2cDgIEWLQ9+wftOs2kPiyo8IEwULGKHW4g+NgxATDuMenxMgK8gcHAdRDgYbhgEO6x2KYOxtFzf5LXB94LttcJATODg4eNn3msyNhBi7j5rjeV8DLzAhtmlfa+8GWwXY1iBepj9kZJmtk\u002FailwInc4IMGcFvvi3bDaOvXfp5cVG\u002F+j63GEcBL\u002FHz7x5rP8PzV4g1g8vG+WAbtL4GjKKFoRrbvnxfJA0pW9i+vnZZWeMou6yFRjYZIn\u002FK8ZCVDOfBh50Wc+TP8clksb2jpVznX8dYfwSy7QbQjra6uWaWWv9VYR002vn5ucXmp7VS0nmfhX+PwHAE3mPGuFAk1CQqTR5TV9HLCe\u002FR23UlrWTKRGt7Gp5z6WcsvMcyQnsH+OSDc+Hjpmrv47X2jitBrjnispCb\u002FQ3kd4FsTyTgbY29FSUv\u002FQ7+19Wzss\u002FM76snZR+pCf++4N39X8jgyJPaJAAA",1793389733734]