\u7814\u7a76\u4e3b\u984c-\u5229\u7528AI\u53ca\u6f14\u7b97\u6cd5\u63d0\u5347\u751f\u7269\u91ab\u7642\u7684\u6aa2\u6e2c\u7cbe\u5ea6<\/p>\n
\u64b0\u5beb\uff1a\u5b78\u751f\u9673\u51a0\u5f6c<\/p>\n
\u96a8\u8457\u96fb\u8166\u7684\u904b\u7b97\u80fd\u529b\u63d0\u5347\uff0c\u6f14\u7b97\u6cd5\u7684\u904b\u7528\u4e5f\u88ab\u5ee3\u6cdb\u4f7f\u7528\uff0c\u800c\u672c\u6240\u7684\u5b8b\u5b54\u5f6c\u6559\u6388\u5373\u662f\u5229\u7528\u4e0d\u540c\u7684\u6f14\u7b97\u6cd5\u4f86\u89e3\u6c7a\u5404\u7a2e\u751f\u7269\u91ab\u7642\u6aa2\u6e2c\u4e0a\u7684\u5b9a\u91cf\u53ca\u5224\u8b80\uff0c\u9032\u800c\u63d0\u5347\u5728\u91ab\u7642\u4e0a\u8a3a\u65b7\u7684\u7cbe\u5ea6\u3002\u4ee5\u4e0b\u6703\u4ecb\u7d39\u5b8b\u8001\u5e2b\u91dd\u5c0d\u4e0d\u540c\u554f\u984c\uff0c\u6240\u63d0\u51fa\u7684\u6f14\u7b97\u6cd5\u7814\u7a76\u3002<\/p>\n
\u9996\u5148\u4ecb\u7d39\u5b8b\u8001\u5e2b\u5728\u4eca\u5e74\u56db\u6708\u520a\u767b\u5728Journal of Biomedical Optics\u7684\u6587\u7ae0-\u201d\u5229\u7528\u5b9a\u91cf\u76f8\u4f4d\u986f\u793a\u6280\u8853\u8868\u5fb5\u53ca\u5224\u65b7\u7d30\u80de\u6b7b\u4ea1\u52d5\u614b\u201d(1.)\u3002\u5728\u85e5\u7269\u958b\u767c\u7684\u6642\u5019\uff0c\u9700\u8981\u7d93\u904e\u4e0d\u540c\u7684\u7be9\u9078\uff0c\u904e\u7a0b\u4e2d\u6703\u5229\u7528\u87a2\u5149\u67d3\u5291\u4f86\u89c0\u6e2c\u4e0d\u540c\u7a2e\u985e\u7684\u7d30\u80de\u6b7b\u4ea1\uff0c\u4ee5\u6b64\u4f86\u7372\u5f97\u85e5\u7269\u7be9\u9078\u6240\u9700\u7684\u91cd\u8981\u8cc7\u8a0a\u3002\u800c\u6b64\u7bc7\u7814\u7a76\u4e2d\u6240\u5229\u7528\u7684\u5b9a\u91cf\u76f8\u4f4d\u986f\u793a\u6280\u8853(Quantitative Phase Imaging,QPI)\u4fbf\u662f\u4e00\u7a2e\u514d\u6a19\u8a18\u4e14\u53ef\u4ee5\u5feb\u901f\u89c0\u6e2c\u7684\u65b9\u6cd5\u3002\u5229\u7528\u5149\u5b78\u7684\u651d\u50cf\u6280\u8853\u52a0\u4e0a\u96fb\u8166\u7a0b\u5f0f\u7684\u8f14\u52a9\u5206\u6790\uff0c\u53ef\u4ee5\u5be6\u73fe\u7d30\u80de\u51cb\u96f6\u7684\u5206\u985e\u5668\u3002\u85c9\u7531\u5206\u6790\u7d30\u80de\u7684\u4e0d\u540c\u53c3\u6578(\u5982:\u7d30\u80de\u5713\u5f62\u6027\u3001\u96e2\u5fc3\u7387\u3001\u5149\u5b78\u9ad4\u7a4d\u7b49\u2026)\u6700\u5f8c\u5f97\u5230\u5206\u985e\u7d50\u679c\u7684\u6700\u4f73\u8868\u73fe\u3002\u5728\u6587\u4e2d\u8868\u660e\uff0c\u5229\u7528QPI\u7684\u6280\u8853\u53ef\u4ee5\u9054\u5230\u7e3d\u9ad4\u5e73\u5747\u9ad8\u905484%\u7684\u6e96\u78ba\u5ea6!<\/p>\n
\u518d\u4f86\u8981\u4ecb\u7d39\u7684\u662f\u5728\u4eca\u5e74\u516d\u6708\u520a\u767b\u5728Frontiers in Physics\u7684\u6587\u7ae0-\u201c\u5229\u7528\u8499\u5730\u5361\u7f85\u6a21\u578b\u4f86\u5be6\u73fe\u975e\u4fb5\u5165\u5f0f\u5b9a\u91cf\u5b50\u5bae\u9838\u9ecf\u819c\u7d44\u7e54\u5167\u5728\u87a2\u5149\u7279\u5fb5\u201d (2.)\u3002\u5b50\u5bae\u9838\u764c\u4e00\u76f4\u4ee5\u4f86\u90fd\u662f\u5973\u6027\u764c\u75c7\u7684\u4e3b\u56e0\u4e4b\u4e00\uff0c\u800c\u6839\u64da\u7814\u7a76\u986f\u793a\uff0c\u5728\u764c\u75c7\u9010\u6f38\u5f62\u6210\u7684\u540c\u6642\uff0c\u5176\u4e2d\u7684NDHD(\u4e00\u7a2e\u8ca0\u8cac\u4eba\u9ad4\u7d30\u80de\u80fd\u91cf\u4ee3\u8b1d\u7684\u529f\u80fd\u86cb\u767d)\u6bd4\u4f8b\u6703\u9010\u6f38\u5347\u9ad8\u3002\u800c\u85c9\u7531\u5b9a\u91cf\u9ecf\u819c\u7d44\u7e54\u4e2d\u7684\u87a2\u5149\u7269\u8cea\u7279\u5fb5\uff0c\u6709\u52a9\u65bc\u5b9a\u91cf\u7d44\u7e54\u4e2d\u7684NDHD\u3002\u800c\u5b8b\u8001\u5e2b\u7684\u5718\u968a\u81f4\u529b\u65bc\u5229\u7528\u5149\u8b5c\u7cfb\u7d71\u4f86\u9032\u884c\u6d3b\u9ad4\u7684\u5b50\u5bae\u9838\u6f2b\u53cd\u5c04\u5149\u8b5c\u4ee5\u53ca\u87a2\u5149\u7269\u8cea\u5b9a\u91cf\uff0c\u5229\u7528\u5149\u8b5c\u7cfb\u7d71\u7684\u597d\u8655\u5728\u65bc\u907f\u514d\u4e86\u50b3\u7d71\u5229\u7528\u7d44\u7e54\u5207\u7247\u7684\u4fb5\u5165\u5f0f\u624b\u6bb5\uff0c\u4e26\u4e14\u80fd\u5920\u66f4\u5168\u9762\u7684\u6aa2\u6e2c\u76ee\u6a19\u7d44\u7e54\u3002\u70ba\u4e86\u5b8c\u6210\u5149\u8b5c\u7684\u64ec\u5408\uff0c\u5229\u7528\u4e86\u8499\u5730\u5361\u7f85\u6a21\u578b(Monte Carlo method,MC)\u4f86\u9032\u884c\u5206\u6790\uff0c\u800c\u5b8b\u8001\u5e2b\u7684\u5718\u968a\u66f4\u5f15\u5165\u4e86\u4eba\u5de5\u795e\u7d93\u7db2\u8def(ANN)\u4f86\u52a0\u901f\u64ec\u5408\u7684\u901f\u5ea6\uff0c\u96d6\u7136\u5728\u6587\u672b\u6307\u51fa\u9019\u6a23\u7684\u65b9\u5f0f\u6e96\u78ba\u5ea6\u4e5f\u8a31\u4e0d\u76e1\u7406\u60f3\uff0c\u4f46\u662f\u85c9\u7531\u9019\u6a23\u7684\u6a21\u64ec\u5206\u6790\u4ecd\u7136\u5f88\u6709\u6f5b\u529b\uff0c\u662f\u53ef\u4ee5\u6301\u7e8c\u958b\u767c\u512a\u5316\u7684\u76ee\u6a19!<\/p>\n
\u6700\u5f8c\u5728\u4eca\u5e74\u516b\u6708\u4e00\u6a23\u520a\u767b\u5728Journal of Biomedical Optics\u7684\u6587\u7ae0-\u201c\u57fa\u65bc\u8499\u5730\u5361\u7f85\u6a21\u578b\u4f86\u9032\u884c\u4eba\u9ad4\u8166\u90e8\u5149\u5b78\u53c3\u6578\u5b9a\u91cf\u7684\u81e8\u5e8a\u5be6\u9a57\uff0c\u5229\u7528\u9023\u7e8c\u8fd1\u7d05\u5916\u5149\u8b5c\u8207\u4e09\u7dad\u6a21\u578b\u201d (3.)\u3002\u5728\u76ee\u524d\u7684\u4eba\u9ad4\u5927\u8166\u7814\u7a76\uff0c\u90fd\u662f\u5229\u7528\u529f\u80fd\u6027\u78c1\u632f\u9020\u5f71(fMRI)\u6216\u662f\u8166\u96fb\u5716(EEG)\u4f86\u505a\u8166\u90e8\u9020\u5f71\uff0c\u4f46\u524d\u8005\u4e0d\u610f\u5206\u8fa8\u6536\u5230\u4fe1\u865f\u7684\u524d\u5f8c\u6642\u9593\uff1b\u5f8c\u8005\u4e0d\u6613\u5206\u8fa8\u6536\u5230\u4fe1\u865f\u7684\u4f86\u6e90\u6df1\u6dfa\u3002\u6240\u4ee5\u5b8b\u8001\u5e2b\u7684\u5718\u968a\u767c\u5c55\u4e86\u5229\u7528\u5149\u5b78\u9032\u884c\u91cf\u6e2c\u7684\u8fd1\u7d05\u5916\u5149\u8b5c(NIRS)\uff0c\u7531\u65bc\u5176\u5149\u5b78\u7684\u7279\u6027\uff0c\u53ef\u4ee5\u9054\u5230\u6bd4EEG\u9084\u4f86\u7684\u66f4\u9ad8\u7a7a\u9593\u89e3\u6790\u5ea6\u4e26\u4e14\u540c\u6a23\u5177\u6709\u8a2d\u5099\u5c0f\u5de7\u53ef\u651c\u7684\u7279\u6027\uff0c\u662f\u6709\u671b\u53d6\u4ee3EEG\u7684\u6280\u8853\u3002\u800c\u57fa\u65bcMC\u6a21\u64ec\u4ee5\u53caANN\u7684\u7d50\u5408\uff0c\u6b64\u7814\u7a76\u53ef\u4ee5\u9054\u523010%\u4ee5\u4e0b\u7684\u8aa4\u5dee\uff0c\u800c\u4e14\u5c07\u6aa2\u6e2c\u6642\u9593\u4e5f\u50c5\u9700\u6578\u5206\u9418\u5373\u53ef\u3002<\/p>\n
\u7d9c\u4e0a\u6240\u8ff0\uff0c\u96fb\u8166\u904b\u7b97\u80fd\u529b\u7684\u63d0\u5347\u5728\u5404\u7a2e\u5c64\u9762\u4e0a\u90fd\u66f4\u63a8\u9032\u4e86\u79d1\u5b78\u7684\u9032\u6b65\uff0c\u85c9\u6b64\u5b8b\u8001\u5e2b\u5c07\u4e4b\u904b\u7528\u5728\u751f\u7269\u91ab\u7642\u6aa2\u6e2c\u7684\u8f14\u52a9\u4e0a\uff0c\u76f8\u4fe1\u660e\u65e5\u91ab\u5b78\u6307\u65e5\u53ef\u5f85!<\/p>\n
<\/p>\n
With the improvement of computation technologies, algorithms have become one of emerging research fields. Professor K.-B. Sung uses different algorithms to solve the quantification and interpretation of various biomedical tests, thereby improving the accuracy of medical diagnosis.<\/p>\n
First of all, Prof. Sung published a work in the Journal of Biomedical Optics in April at this year- “Characterization and identification of cell death dynamics by quantitative phase imaging.” During drug development, in this work, the progression of cell death, e.g. the generation of extracellular vesicles during apoptosis, has been investigated for a comprehensive understanding of cell responses with Quantitative phase imaging (QPI). QPI is a label-free imaging technique that records the phase distribution of a cell resulting from both the intracellular refractive index and cell thickness. This study applies QPI to classify apoptotic, necrotic, and normal cells simultaneously. It characterizes the dynamics of morphological and quantitative-phase features in the cell death process. In conclusion, this study showed 84.0% overall accuracy in classifying normal cells.<\/p>\n
Prof. Sung has also published another works in Frontiers in Physics in June of this year-“Non-Invasive Quantification of Layer-Specific Intrinsic Fluorescence From Mucosa of the Uterine Cervix Using Monte-Carlo-Based Models.” Previously, many in-vivo studies showed differences in the intensity and\/or shape of fluorescence emission from the mucosa in more accessible organ sites such as in the digestive tract and urogenital system. These may provide helpful information for the early detection of epithelial cancers or their precursors. And major fluorophores in the mucosa that are related to cancerization include reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) found predominately in mitochondria of cells. Using Monte Carlo (MC) simulations of fluorescence excitation and emission processes has advantages of being flexible and versatile because they can accommodate geometric specifications of any experimental arrangement and tissue heterogeneity. In this study, Prof. Sung combined MC simulations and artificial neural networks (ANNs) to reduce processing time. Regardless of the sensitivity of detecting cervical precancers, using intrinsic fluorescence alone may not be sufficient. The time required for extracting tissue’s optical properties could be accelerated by a fluorescence ANN forward model and optimizing the processing speed. Moreover, spectra captured from scanning a large tissue area could be analyzed simultaneously through parallel operations to develop this method as an instant diagnostic tool.<\/p>\n
Finally, Prof. Sung published a wrok in the Journal of Biomedical Optics in August this year- ” Quantifying tissue’s optical properties of human heads in vivo using continuous-wave near-infrared spectroscopy and subject-specific three-dimensional Monte Carlo models.” Human brain activities have long been of great interest to many fields, stretching from fundamental neuroscience, branches of medicine, and education to even the brain-computer interface. Functional magnetic resonance imaging (fMRI) is the standard gold method of brain activity monitoring with great three-dimensional (3D) spatial resolution over the whole brain. However, the temporal resolution of fMRI is low, and the subject or patient is restricted to the supine position in an MRI scanner, which is expensive and not readily accessible. Functional near-infrared spectroscopy (fNIRS) employs low-cost and compact instruments to monitor brain activities with moderate temporal and spatial resolution. This study aimed to use a multidistance continuous-wave (CW) NIRS system to quantify the scalp, skull, and GM’s (gray matter) optical properties (Ops) in the human head in-vivo. In the end, the average error between ANN outputs and corresponding MC simulations was under 10%! Moreover, the curve fitting could be done in several minutes with the help of the ANNs.<\/p>\n
In conclusion, the improvement of computing has further promoted the progress of science at various levels. I believe that the future of medicine is just around the corner!<\/p>\n
<\/p>\n
Ref:<\/p>\n
\u7814\u7a76\u4e3b\u984c-\u5229\u7528AI\u53ca\u6f14\u7b97\u6cd5\u63d0\u5347\u751f\u7269\u91ab\u7642\u7684\u6aa2\u6e2c\u7cbe\u5ea6 \u64b0\u5beb\uff1a\u5b78\u751f\u9673\u51a0\u5f6c \u96a8\u8457\u96fb\u8166\u7684\u904b\u7b97\u80fd\u529b\u63d0\u5347\uff0c\u6f14\u7b97\u6cd5\u7684\u904b\u7528\u4e5f\u88ab\u5ee3 […]\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[19],"tags":[],"class_list":["post-2065","post","type-post","status-publish","format-standard","hentry","category-award"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=\/wp\/v2\/posts\/2065","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2065"}],"version-history":[{"count":1,"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=\/wp\/v2\/posts\/2065\/revisions"}],"predecessor-version":[{"id":2066,"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=\/wp\/v2\/posts\/2065\/revisions\/2066"}],"wp:attachment":[{"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2065"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2065"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bebi.ntu.edu.tw\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2065"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}