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RISS 인기검색어
- 검색키워드
- 저자 : Shoji Nagao (검색결과 4 건)
- 무료
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- 유료
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Detection of Abnormal Candidate Regions on Temporal Subtraction Images Based on DCNN
Mitsuaki NAGAO,Noriaki MIYAKE,Yuriko YOSHINO,Huimin LU,Joo Kooi TAN,Hyoungseop KIM,Seiichi MURAKAMI,Takatoshi AOKI,Yasushi HIRANO,Shoji KIDO 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10
Cancer is a leading cause of death both in Japan and worldwide. Detection of cancer region in CT images is the most important task to early detection. Recently, visual screening based on CT images become useful tools for cancer detection. However, due to the large number of images and the complexity of the image processing algorithms, image processing technique is still required a high screening quality. To overcome this problem, some computer aided diagnosis (CAD) algorithms are proposed. In this paper, we have designed and developed a framework combining machine learning based on deep convolutional neural networks (DCNN) and temporal subtraction techniques based on non-rigid image registration algorithm. Our main classification method can be built into three main steps; i) pre-processing for image segmentation, ii) image matching for registration, and iii) classification of abnormal regions based on machine learning algorithms. We performed our proposed technique to 25 thoracic MDCT sets and obtained true positive rates of 92.31 [%], false positive rates of 6.32 [/case] were obtained.
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Detection of Abnormal Shadows on Temporal Subtraction Images Based on Multi-phase CNN
Mitsuaki NAGAO,Noriaki MIYAKE,Yuriko YOSHINO,Huimin LU,Hyoungseop KIM,Seiichi MURAKAMI,Takatoshi AOKI,Shoji KIDO 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
Recently, visual screening based on CT images become useful tools in the medical fields. However, due to the large number of images and the complexity of the image processing algorithms, image processing technique for the high screening quality is still required. To overcome this problem, some computer aided diagnosis (CAD) algorithms are proposed. Cancer is a leading cause of death both in Japan and worldwide. Detection of cancer region in CT images is the most important task to early detection and early treatment. We have designed and developed a framework combining machine learning based on multi-phase convolutional neural networks (CNN) and temporal subtraction techniques based on non-rigid image registration algorithm. Our main classification method can be built into three main steps; i) preprocessing for image segmentation, ii) image matching for registration, and iii) classification of abnormal regions based on machine learning algorithms. We performed our proposed technique to 25 thoracic MDCT sets and obtained true positive rates of 93.55%, false positive rates of 10.93 /case.
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Kazuhiro Takehara,Takashi Matsumoto,Junzo Hamanishi,Kosei Hasegawa,Motoki Matsuura,Kiyonori Miura,Shoji Nagao,Hidekatsu Nakai,Naotake Tanaka,Hideki Tokunaga,Kimio Ushijima,Hidemichi Watari,Yoshihito Y 대한부인종양학회 2021 Journal of Gynecologic Oncology Vol.32 No.2
Objective: The primary objective of this study was to evaluate the safety of niraparib 300 mg/dayin Japanese patients with platinum-sensitive, relapsed ovarian cancer in a maintenance setting. Methods: Phase 2, multicenter, open-label, single-arm study enrolled Japanese patients withplatinum-sensitive, relapsed ovarian cancer who had received ≥2 platinum-based regimens. The primary endpoint (incidence of grade 3 or 4 thrombocytopenia-related events within 30days after initial niraparib administration) was justified by the incidences of a global pivotalphase 3 study and its post-hoc safety analysis on thrombocytopenia, the major hematologicaladverse event of niraparib. The overall safety analysis examined other treatment-emergentadverse events (TEAEs). Results: Enrolled patients (n=19) had a median (min, max) body weight of 53.9 (40.8–79.1)kg; all but one patient weighed <77 kg. Most (94.7%) patients initially received niraparib300 mg/day but this decreased in subsequent cycles (mean±standard deviation doseintensity, 191.6±65.7 mg/day). In total, 6/19 (31.6%) patients experienced grade 3 or 4 thrombocytopenia-related events within 30 days of initial niraparib administration. Other common TEAEs included nausea, and decreased platelet or neutrophil counts. Noprogression-free or overall survival events occurred; only 1 of 4 response-evaluable patientshad a post-baseline tumor assessment (stable disease). Conclusion: The incidence of grade 3 or 4 thrombocytopenia-related events in Japaneseovarian cancer patients was similar to that in the corresponding non-Japanese study. Overall,the safety profile was acceptable and consistent with the known safety profile and previousexperience with niraparib. Trial Registration: ClinicalTrials.gov Identifier: NCT03759587
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Keiichi Fujiwara,Hiroyuki Fujiwara,Hiroyuki Yoshida,Toyomi Satoh,Kan Yonemori,Shoji Nagao,Takashi Matsumoto,Hiroaki Kobayashi,Hughes Bourgeois,Philipp Harter,Anna Maria Mosconi,Isabel Palacio Vazquez 대한부인종양학회 2021 Journal of Gynecologic Oncology Vol.32 No.5
Objective: The addition of maintenance olaparib to bevacizumab demonstrated a significant progression-free survival (PFS) benefit in patients with newly diagnosed, advanced ovarian cancer in the PAOLA-1/ENGOT-ov25 trial (NCT02477644). We evaluated maintenance olaparib plus bevacizumab in the Japan subset of PAOLA-1. Methods: PAOLA-1 was a randomized, double-blind, phase III trial. Patients received maintenance olaparib tablets 300 mg twice daily or placebo twice daily for up to 24 months, plus bevacizumab 15 mg/kg every 3 weeks for up to 15 months in total. This prespecified subgroup analysis evaluated investigator-assessed PFS (primary endpoint). Results: Of 24 randomized Japanese patients, 15 were assigned to olaparib and 9 to placebo. After a median follow-up for PFS of 27.7 months for olaparib plus bevacizumab and 24.0 months for placebo plus bevacizumab, median PFS was 27.4 versus 19.4 months, respectively (hazard ratio [HR]=0.34; 95% confidence interval [CI]=0.11–1.00). In patients with tumors positive for homologous recombination deficiency, the HR for PFS was 0.57 (95% CI=0.16–2.09). Adverse events in the Japan subset were generally consistent with those of the PAOLA-1 overall population and with the established safety and tolerability profiles of olaparib and bevacizumab. Conclusion: Results in the Japan subset of PAOLA-1 support the overall conclusion of the PAOLA-1 trial demonstrating that the addition of maintenance olaparib to bevacizumab provides a PFS benefit in patients with newly diagnosed, advanced ovarian cancer. Trial Registration: ClinicalTrials.gov Identifier: NCT02477644
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