{"id":691,"date":"2023-07-01T11:31:36","date_gmt":"2023-07-01T02:31:36","guid":{"rendered":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/?page_id=691"},"modified":"2023-07-13T14:40:27","modified_gmt":"2023-07-13T05:40:27","slug":"achievement-2019","status":"publish","type":"page","link":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/en\/achievement-2019\/","title":{"rendered":"Achievement-2019"},"content":{"rendered":"\n<h2 class=\"wp-block-heading blue-line\">Original Papers<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Kadoya N, Abe K, Nemoto H, Sato K, Ieko Y, Ito K, Dobashi S, Takeda K, Jingu K, \u201cEvaluation of a 3D-printed Heterogeneous Anthropomorphic Head and Neck Phantom for Patient-Specific Quality Assurance in Intensity-Modulated Radiation Therapy\u201d, Radiol Phys Technol. 2019 Sep;12(3):351-356<\/li>\n\n\n\n<li>Kajikawa T, Kadoya N, Ito K, Takayama Y, Chiba T, Tomori S, Nemoto H, Dobashi S, Takeda K, Jingu K, \u201cA Convolutional Neural Network Approach for IMRT Dose Distribution Prediction in Prostate Cancer Patients\u201d, J Radiat Res. 2019 Oct 23;60(5):685-693<\/li>\n\n\n\n<li>Kadoya N, \u201cDeformable Image Registration and Auto-Segmentation for Various Medical Imaging Types\u201d, Igaku Butsuri. 2019;39(1):12-19<\/li>\n\n\n\n<li>Kadoya N, Kito S, Kurooka M, Saito M, Takemura A, Tohyama N, Tominaga M, Nakajima Y, Fujita Y, Miyabe Y, \u201cFactual Survey of the Clinical Use of Deformable Image Registration Software for Radiotherapy in Japan\u201d, J Radiat Res. 2019 Jul 1;60(4):546-553<\/li>\n\n\n\n<li>Kadoya N, Abe Y, Kajikawa T, Ito K, Yamamoto T, Umezawa R, Chiba T, Katsuta Y, Takayama Y, Kato T, Kikuchi Y, Jingu K, \u201cAutomated noncoplanar treatment planning strategy in stereotactic radiosurgery of multiple cranial metastases: HyperArc and CyberKnife dose distributions\u201d, Med Dosim. 2019 Feb 28. pii: S0958-3947(19)30029-9<\/li>\n\n\n\n<li>Tanaka S, Kadoya N, Kajikawa T, Matsuda S, Dobashi S, Takeda K, Jingu K, \u201cInvestigation of thoracic four-dimensional CT-based dimension reduction technique for extracting the robust radiomic features\u201d, Phys Med. 2019 Feb;58:141-148<\/li>\n\n\n\n<li>Kipritidis J, Tahir BA, Cazoulat G, Hofman MS, Siva S, Callahan J, Hardcastle N, Yamamoto T, Christensen GE, Reinhardt JM, Kadoya N, Patton TJ, Gerard SE, Duarte I, Archibald-Heeren B, Byrne M, Sims R, Ramsay S, Booth JT, Eslick E, Hegi-Johnson F, Woodruff HC, Ireland RH, Wild JM, Cai J, Bayouth JE, Brock K, Keall PJ, \u201ce VAMPIRE challenge: A multi-institutional validation study of CT ventilation imaging\u201d, Med Phys. 2019 Mar;46(3):1198-1217<\/li>\n\n\n\n<li>Hashimoto S, Nakajima Y, Kadoya N, Abe K, Karasawa K, \u201cEnergy dependence of a radiophotoluminescent glass dosimeter for HDR 192 Ir brachytherapy source\u201d, Med Phys. 2019 Feb;46(2):964-972<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Domestic Conference<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u7d30\u8c37\u7950\u91cc\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u6839\u672c\u5149\u3001\u7530\u4e2d\u7965\u5e73\u3001\u677e\u7530\u5320\u5e73\u3001\u6b66\u7530\u8ce2\u3001\u571f\u6a4b\u5353\u3001\u795e\u5bae\u5553\u4e00\u3001\u4e2d\u6751\u5149\u5b8f. \u201cDIR end-to-end\u7269\u7406\u30d5\u30a1\u30f3\u30c8\u30e0\u306e\u81e8\u5e8a\u7684\u6709\u7528\u6027\u306e\u691c\u8a0e\u201d, \u7b2c32\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2019.11 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>\u6c60\u7530\u9f8d\u592a\u90ce\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u83c5\u539f\u5eb7\u6674\u3001\u6e0b\u5b5d\u4e4b\u3001\u77f3\u4e95\u4f38\u3001\u795e\u5bae\u5553\u4e00. \u201c\u52d5\u4f53\u53ef\u5909\u578b\u30d5\u30a1\u30f3\u30c8\u30e0\u3092\u7528\u3044\u305f\u69d8\u3005\u306aCT\u64ae\u50cf\u6761\u4ef6\u306b\u3088\u308bDIR\u7cbe\u5ea6\u8a55\u4fa1\u201d, \u7b2c32\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2019.11 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>\u4f0a\u85e4\u8b19\u543e\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u52dd\u7530\u7fa9\u4e4b\u3001\u5343\u8449\u8cb4\u4ec1\u3001\u6885\u6fa4\u73b2\u3001\u677e\u4e0b\u6674\u96c4\u3001\u795e\u5bae\u5553\u4e00. \u201cMRI-Linac\u7528CCC-based\u7dda\u91cf\u8a08\u7b97\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u6709\u52b9\u6027\u201d, \u7b2c32\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2019.11 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b\u3001\u7d30\u8c37\u7950\u91cc\u3001\u6839\u672c\u5149\u3001\u7530\u4e2d\u7965\u5e73\u3001\u677e\u7530\u5320\u5e73\u3001\u6b66\u7530\u8ce2\u3001\u571f\u6a4b\u5353\u3001\u795e\u5bae\u5553\u4e00\u3001\u4e2d\u6751\u5149\u5b8f. \u201cDIR\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u306eEnd to end\u8a66\u9a13\u7528\u7269\u7406\u30d5\u30a1\u30f3\u30c8\u30e0\u306e\u958b\u767a\u201d, \u7b2c32\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2019.11 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>\u52dd\u7530\u7fa9\u4e4b\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u4f0a\u85e4\u8b19\u543e\u3001\u5343\u8449\u8cb4\u4ec1\u3001\u677e\u4e0b\u6674\u96c4\u3001\u795e\u5bae\u5553\u4e00. \u201c\u8907\u56de\u8ee2\u304a\u3088\u3073\u5358\u56de\u8ee2\u982d\u981a\u90e8VMAT\u306b\u304a\u3051\u308b\u4e88\u5f8c\u4e88\u6e2c\u201d, \u7b2c32\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2019.11 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>Sakulsingharoj S, Kadoya N, Matsuda S, Tanaka S, Jingu K. \u201cEvaluation of deformable image registration accuracy for brachytherapy using two different commercial software in cervical cancer\u201d, \u7b2c32\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2019.11 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>\u7530\u908a\u4fca\u5e73\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u7530\u4e2d\u7965\u5e73\u3001\u68b6\u5ddd\u667a\u535a\u3001\u963f\u90e8\u5e78\u592a\u3001\u6b66\u7530\u8ce2\u3001\u571f\u6a4b\u5353\u3001\u795e\u5bae\u5553\u4e00. \u201cDeep learning based radiomics \u3092\u7528\u3044\u305f\u975e\u5c0f\u7d30\u80de\u80ba\u304c\u3093\u306e\u4e88\u5f8c\u4e88\u6e2c\u30e2\u30c7\u30eb\u306e\u958b\u767a\u201d, \u7b2c32\u56de\u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2019.11 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>Tanaka S, Kadoya N, Nakane K, Kajikawa T, Abe K, Dobashi S, Takeda K, Jingu K, \u201cHomology as novel radiomic features for prediction of the prognosis of lung cancer based on CT-based radiomics\u201d, \u7b2c117\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2018.4 \u6a2a\u6d5c<\/li>\n\n\n\n<li>Nemoto H, Kadoya N, Kajikawa T, Nakajima Y, Kanai T, Ieko Y, Takeda K, Jingu K, \u201c4D-CBCT ventilation image-based VMAT plans are comparable to 4D-CT ventilation image-based plans : Evaluating 4D-CBCT ventilation images\u201d, \u7b2c117\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2018.4 \u6a2a\u6d5c<\/li>\n\n\n\n<li>Takagi H, Kadoya N, Kajikawa T, Tanaka S, Takayama Y, Chiba T, Ito K, Dobashi S, Takeda K, Jingu K, \u201cDevelopment of multi-atlas based intra-prostatic urethra auto-segmentation using machine learning for prostate cancer radiotherapy\u201d, \u7b2c117\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a. 2018.4 \u6a2a\u6d5c<\/li>\n\n\n\n<li>\u68b6\u5ddd\u667a\u535a\u3001\u89d2\u8c37\u502b\u4e4b\u3001\u9ad8\u5c71\u4f73\u6a39\u3001\u6238\u68ee\u8056\u6cbb\u3001\u4f0a\u85e4\u8b19\u543e\u3001\u5343\u8449\u8cb4\u4ec1\u3001\u571f\u6a4b\u5353\u3001\u6b66\u7530\u8ce2\u3001\u795e\u5bae \u5553\u4e00. \u201c\u524d\u7acb\u817a\u764c\u306b\u304a\u3051\u308bIMRT\u306b\u5bfe\u3059\u308b\u7573\u307f\u8fbc\u307f\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u57fa\u3065\u304f\u7dda\u91cf\u5206\u5e03\u4e88\u6e2c\u6cd5\u306e\u8a55\u4fa1\u201d. \u7b2c32\u56de\u9ad8\u7cbe\u5ea6\u653e\u5c04\u7dda\u5916\u90e8\u7167\u5c04\u90e8\u4f1a\u5b66\u8853\u5927\u4f1a. 2019. 3 \u6771\u4eac<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">International Conference<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Matsuda S, Kadoya N, Ito K,\u3000Tanaka S, Tanabe S, Takayama Y, Tomori S, Dobashi S, Takeda K, Jingu K, \u201cDevelopment of convolutional neural network-based automated segmentation using evolutionary algorithm on prostate MR images\u201d, 19th Asia-Oceania Congress of Medical Physics (AOCMP), 2019. 10 Perth, Australia<\/li>\n\n\n\n<li>Nemoto H, Kadoya N, Tanaka S, Chiba T, Katsuta Y, Matsuda S, Ito K, Dobashi S, Takeda K, Umezawa R, Jingu K, \u201cEvaluation of 3D-printed heterogeneous anthropomorphic thorax phantom for patient-specific quality assurance in intensity-modulated radiation therapy\u201d, 19th Asia-Oceania Congress of Medical Physics (AOCMP), 2019. 10 Perth, Australia<\/li>\n\n\n\n<li>Tanaka S, Kadoya N, Nemoto H, Chiba T, Katsuta Y, Matsuda S, Ito K, Dobashi S, Takeda K, Umezawa R, Jingu K, \u201cDosimetric impact of heart functional based planning in esophageal cancer patients\u201d, 19th Asia-Oceania Congress of Medical Physics (AOCMP), 2019. 10 Perth, Australia<\/li>\n\n\n\n<li>Nemoto H, Kadoya N, Kajikawa T, Nakajima Y, Kanai T, Ieko Y, Jingu K. \u201cEvaluation of factors that affect 4D Cone Beam CT ventilation images for adaptive functional avoidance radiotherapy\u201d, 61th annual meeting of AAPM, 2019.7. San Antonio, USA<\/li>\n\n\n\n<li>Tanaka S, Kadoya N, Kajikawa T, Abe K, Yamamoto T, Takahashi N, Takeda K, Dobashi S, Takeda K, Jingu K. \u201cPrognosis prediction with Homology-based radiomic features quantifying the lung tumor malignancy in CT-based radiomics\u201d, 61th annual meeting of AAPM, 2019.7. San Antonio, USA<\/li>\n\n\n\n<li>Abe K, Kadoya N, Tanaka S, Nakajima Y, Hashimoto S, Kajikawa T, Karasawa K, Jingu K. \u201cThe feasibility of MVCT-based radiomics for Delta-radiomics in head and neck cancer\u201d, 61th annual meeting of AAPM, 2019.7. San Antonio, USA<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Award<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u6839\u672c\u5149, \u7b2c117\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a\u3000\u5927\u4f1a\u9577\u8cde (\u30b4\u30fc\u30eb\u30c9)<\/li>\n\n\n\n<li>\u7530\u4e2d\u7965\u5e73, \u7b2c117\u56de\u65e5\u672c\u533b\u5b66\u7269\u7406\u5b66\u4f1a\u5b66\u8853\u5927\u4f1a\u3000\u5927\u4f1a\u9577\u8cde (\u30b7\u30eb\u30d0\u30fc)<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Patent<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u89d2\u8c37\u502b\u4e4b\u3001\u6839\u672c\u5149\u3001\u963f\u90e8\u5e78\u592a\u3001\u7530\u4e2d\u7965\u5e73\u3001\u7d30\u8c37\u7950\u91cc\u3001\u795e\u5bae\u5553\u4e00\u3001\u4e2d\u6751\u5149\u5b8f. \u201d\u975e\u525b\u4f53\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u8abf\u6574\u652f\u63f4\u88c5\u7f6e\u201d, \u7279\u98582019-209949<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Invited talk &amp; Symposium<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u653e\u5c04\u7dda\u6cbb\u7642\u306b\u304a\u3051\u308bMR\u753b\u50cf\u306e\u5229\u7528\u201d. \u533b\u5b66\u7269\u7406\u30bb\u30df\u30ca\u30fc\u540d\u53e4\u5c4b, 2019.12 \u540d\u53e4\u5c4b<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u80ba\u764c\u60a3\u8005\u306eCT\u753b\u50cf\u306b\u5bfe\u3059\u308b\u4f4d\u76f8\u5e7e\u4f55\u5b66\u7684\u6982\u5ff5\u3092\u7528\u3044\u305f\u4e88\u5f8c\u89e3\u6790\u6cd5\u201d. \u660e\u6cbb\u5927\u5b66\u5171\u540c\u5229\u7528\u30fb\u5171\u540c\u7814\u7a76\u62e0\u70b9\u7814\u7a76\u96c6\u4f1a\u300cAI\u3092\u7528\u3044\u305f\u533b\u7642\u753b\u50cf\u89e3\u6790\u306e\u73fe\u72b6\u3068\u8ab2\u984c\u300d, 2019.11 \u6771\u4eac&nbsp;<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u6700\u65b0\u533b\u7528\u753b\u50cf\u6280\u8853-DIR\u3068AI\u3068\u653e\u5c04\u7dda\u6cbb\u7642\u201d. 2019\u5e74\u5ea6\u653e\u5c04\u7dda\u6cbb\u7642\u61c7\u8a71\u4f1a \u7b2c2\u56de\u5b9a\u4f8b\u4f1a. 2019.11 \u6771\u4eac<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cDIR\u306e\u6982\u8981\u201d. \u65e5\u672c\u533b\u5b66\u7269\u7406\u58eb\u4f1a\u3000\u7b2c7\u56deDIR\u5b9f\u6280\u8b1b\u7fd2\u4f1a. 2019.9 \u6771\u4eac<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u6a5f\u68b0\u5b66\u7fd2\u3068MIM-DIR\u3092\u7d44\u307f\u5408\u308f\u305b\u305f\u524d\u7acb\u817a\u5185\u5c3f\u9053\u4f4d\u7f6e\u63a8\u5b9a\u6cd5\u306e\u958b\u767a\u201d. \u7b2c8\u56deMIM Maestro\u30e6\u30fc\u30b6\u30fc\u30ba\u30df\u30fc\u30c6\u30a3\u30f3\u30b0. 2019.6 \u6771\u4eac<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u5c0f\u7dda\u6e90\u6cbb\u7642\u306b\u304a\u3051\u308bdeformable image registration\u201d. \u65e5\u672c\u653e\u5c04\u7dda\u816b\u760d\u5b66\u4f1a\u5c0f\u7dda\u6e90\u6cbb\u7642\u90e8\u4f1a\u7b2c21\u56de\u5b66\u8853\u5927\u4f1a \u30b7\u30f3\u30dd\u30b8\u30a6\u30e01 \u7269\u7406\u5b66\u7684\u80cc\u666f\u304b\u3089\u307f\u305f\u6a19\u6e96\u5316. 2019.5 \u5fb3\u5cf6<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u653e\u5c04\u7dda\u6cbb\u7642\u306b\u304a\u3051\u308bAI\u306e\u52d5\u5411\u201d. \u7b2c53\u56de\u81e8\u5e8a\u533b\u5b66\u7269\u7406\u7814\u7a76\u4f1a. 2019. 3 \u6771\u4eac<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u9069\u5fdc\u653e\u5c04\u7dda\u6cbb\u7642\u201d. \u7b2c7\u56deJASTRO\u653e\u5c04\u7dda\u6cbb\u7642\u30fb\u7269\u7406\u5b66\u30bb\u30df\u30ca\u30fc. 2019. 3 \u4ed9\u53f0<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cDIR\u306e\u81e8\u5e8a\u5fdc\u7528\u201d. \u7fa4\u99ac\u653e\u5c04\u7dda\u6280\u8853\u7814\u7a76\u4f1a. 2019.3 \u524d\u6a4b<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u30ec\u30c7\u30a3\u30aa\u30df\u30af\u30b9&#8221;\u304c\u653e\u5c04\u7dda\u6cbb\u7642\u306b\u3084\u3063\u3066\u304d\u305f\uff01\uff5e\u3053\u308c\u307e\u3067\u306e\u5e38\u8b58\u304c\u5909\u308f\u308b\uff5e\u201d, \u5fb3\u5cf6\u5927\u5b66\u304c\u3093\u30d7\u30ed\u30bb\u30df\u30ca\u30fc. 2019. 3 \u5fb3\u5cf6<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cAdaptive radiotherapy\u306e\u6700\u524d\u7dda-ART\u306f\u3069\u3053\u307e\u3067\u9032\u6b69\u3057\u3001\u4eca\u5f8c\u3069\u3046\u306a\u308b\u304b\uff1f\u201d, \u7b2c32\u56de\u9ad8\u7cbe\u5ea6\u653e\u5c04\u7dda\u5916\u90e8\u7167\u5c04\u90e8\u4f1a\u5b66\u8853\u5927\u4f1a. 2019. 3 \u6771\u4eac<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cDIR\u306e\u6982\u8981\u201d. \u65e5\u672c\u533b\u5b66\u7269\u7406\u58eb\u4f1a\u533b\u5b66\u7269\u7406\u58eb\u30bb\u30df\u30ca\u30fcDIR\u5b9f\u6280\u8b1b\u7fd2\u4f1a. 2019.2 \u6771\u4eac<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cDIR\u306e\u6982\u8981\u201d. \u65e5\u672c\u533b\u5b66\u7269\u7406\u58eb\u4f1a\u3000\u7b2c6\u56deDIR\u5b9f\u6280\u8b1b\u7fd2\u4f1a. 2019.2 \u6771\u4eac<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201cART\u306b\u304b\u304b\u305b\u306a\u3044DIR:\u9650\u754c\u3068\u5c06\u6765\u5c55\u671b\u201d, \u7b2c1\u56de\u5175\u5eab\u306e\u653e\u5c04\u7dda\u6cbb\u7642\u306e\u672a\u6765\u3092\u304b\u305f\u308b\u4f1a 2019.2<\/li>\n\n\n\n<li>\u89d2\u8c37\u502b\u4e4b. \u201c\u653e\u5c04\u7dda\u6cbb\u7642\u8a08\u753b\u652f\u63f4\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u306b\u3064\u3044\u3066\u201d. \u6771\u4eac\u653e\u5c04\u7dda\u6cbb\u7642\u6280\u8853\u7814\u7a76\u4f1a 2019.1<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading blue-line\">Grant<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u79d1\u5b66\u7814\u7a76\u8cbb\u88dc\u52a9\u91d1\u3000\u57fa\u76e4C \u300cRadiomics\u6280\u8853\u3092\u7528\u3044\u3066CT\u753b\u50cf\u306e\u307f\u304b\u3089\u80ba\u6a5f\u80fd\u753b\u50cf\u3092\u4f5c\u6210\u3059\u308b\u624b\u6cd5\u306e\u958b\u767a\u300d(2019\u5e744\u6708\uff5e2021\u5e743\u6708\u3001\u7814\u7a76\u4ee3\u8868\u8005\u3000\u89d2\u8c37\u502b\u4e4b 429\u4e07\u5186\uff09<\/li>\n\n\n\n<li>\u79d1\u5b66\u7814\u7a76\u8cbb\u88dc\u52a9\u91d1\u3000\u82e5\u624b\u7814\u7a76 \u300c\u53ef\u5909\u578b\u30de\u30eb\u30c1\u30c1\u30e3\u30f3\u30cd\u30eb\u30a2\u30d7\u30ea\u30b1\u30fc\u30bf\u3092\u7528\u3044\u305f\u5f37\u5ea6\u5909\u8abf\u5c0f\u7dda\u6e90\u6cbb\u7642\u6cd5\u306e\u958b\u767a\u300d(2019\u5e744\u6708\uff5e2021\u5e743\u6708\u3001\u7814\u7a76\u4ee3\u8868\u8005\u3000\u5343\u8449\u8cb4\u4ec1 403\u4e07\u5186\uff09<\/li>\n\n\n\n<li>\u79d1\u5b66\u7814\u7a76\u8cbb\u88dc\u52a9\u91d1\u3000\u82e5\u624b\u7814\u7a76 \u300cRadiomics\u89e3\u6790\u3092\u5fdc\u7528\u3055\u305b\u305f\u9ad8\u7cbe\u5ea6\u753b\u50cf\u30ec\u30b8\u30b9\u30c8\u30ec\u30fc\u30b7\u30e7\u30f3\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306e\u958b\u767a\u300d(2019\u5e744\u6708\uff5e2020\u5e743\u6708\u3001\u7814\u7a76\u4ee3\u8868\u8005\u3000\u5bb6\u5b50\u7fa9\u6717 416\u4e07\u5186\uff09<\/li>\n\n\n\n<li>\u516c\u76ca\u8ca1\u56e3\u6cd5\u4eba\u304c\u3093\u7814\u7a76\u632f\u8208\u8ca1\u56e3\u304c\u3093\u7814\u7a76\u52a9\u6210\u91d1\u3000(2019\u5e744\u6708\uff5e2020\u5e743\u6708\u3001\u7814\u7a76\u4ee3\u8868\u8005\u3000\u52dd\u7530\u7fa9\u4e4b 50\u4e07\u5186\uff09<\/li>\n\n\n\n<li>\u516c\u76ca\u8ca1\u56e3\u6cd5\u4eba\u304c\u3093\u7814\u7a76\u632f\u8208\u8ca1\u56e3\u304c\u3093\u7814\u7a76\u52a9\u6210\u91d1\u3000(2019\u5e744\u6708\uff5e2020\u5e743\u6708\u3001\u7814\u7a76\u4ee3\u8868\u8005\u3000\u963f\u90e8\u5e78\u592a 50\u4e07\u5186\uff09<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Original Papers Domestic Conference International Conference Award Patent Invited talk &amp; Symposium Grant<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-achievement.php","meta":{"_locale":"en_US","_original_post":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/?page_id=437","footnotes":""},"class_list":["post-691","page","type-page","status-publish","hentry","en-US"],"_links":{"self":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages\/691","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/comments?post=691"}],"version-history":[{"count":7,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages\/691\/revisions"}],"predecessor-version":[{"id":1246,"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/pages\/691\/revisions\/1246"}],"wp:attachment":[{"href":"https:\/\/www.rt-medphys.med.tohoku.ac.jp\/wp-json\/wp\/v2\/media?parent=691"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}