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Actual Use of Rigid Hysteroscope Intrauterine BIGATTI Shaver (IBS<sup>®</sup>) with a Morcellator System
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作者 Toshiyuki Kakinuma Kaoru Kakinuma +8 位作者 Ayano Shimizu Takahum Okusa Eri Suizu Masataka Kagimoto masaki abe Koyomi Saito Michitaka Ohwada Nobuhiro Takeshima Kaoru Yanagida 《Open Journal of Obstetrics and Gynecology》 2021年第11期1494-1499,共6页
Hysteroscopic resection of endometrial lesions has recently gained popularities. We here report the usefulness and safety of hysteroscopic surgery using Intrauterine BIGATTI Shaver (IBS<span style="font-size:1... Hysteroscopic resection of endometrial lesions has recently gained popularities. We here report the usefulness and safety of hysteroscopic surgery using Intrauterine BIGATTI Shaver (IBS<span style="font-size:10.0pt;font-family:""><sup></span><span style="font-size:10.5pt;font-family:"color:#4F4F4F;background:white;">&reg;</span><span style="font-size:10.0pt;font-family:""></sup></span><span>). We performed this surgery for 6 patients: 4 endometrial polyps and 2 intrauterine myoma. The average operation time was 25.7</span><span "=""> </span><span>±</span><span "=""> </span><span>13.2 minutes. Only a small amount of bleeding was noted in all cases. There were no surgical complications. Two out of four patients who desired childbearing became pregnant. Hysteroscopic surgery using IBS<span style="font-size:10.0pt;font-family:""><sup></span><span style="font-size:10.5pt;font-family:"color:#4F4F4F;background:white;">&reg;</span><span style="font-size:10.0pt;font-family:""></sup></span></span><span> can safely and reliably remove intrauterine protruding lesions under aspiration without using a heat source. Less endometrial damage may help preserve fertility.</span> 展开更多
关键词 Hysteroscopic Surgery Morcellator Uterine Submucosal Fibroids Endometrial Polyps
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PID3Net:a deep learning approach for single-shot coherent X-ray diffraction imaging of dynamic phenomena
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作者 Tien-Sinh Vu Minh-Quyet Ha +17 位作者 Adam Mukharil Bachtiar Duc-Anh Dao Truyen Tran Hiori Kino Shuntaro Takazawa Nozomu Ishiguro Yuhei Sasaki masaki abe Hideshi Uematsu Naru Okawa Kyosuke Ozaki Kazuo Kobayashi Yoshiaki Honjo Haruki Nishino Yasumasa Joti Takaki Hatsui Yukio Takahashi Hieu-Chi Dam 《npj Computational Materials》 2025年第1期684-697,共14页
This paper introduces a deep learning (DL)-based method for phase retrieval tailored to single-shot, multiple-frame coherent X-ray diffraction imaging (CXDI), designed specifically for visualizing local nanostructural... This paper introduces a deep learning (DL)-based method for phase retrieval tailored to single-shot, multiple-frame coherent X-ray diffraction imaging (CXDI), designed specifically for visualizing local nanostructural dynamics within a larger sample. Current phase retrieval methods often struggle with achieving high spatiotemporal resolutions, handling dynamic imaging, and managing computational costs, which limits their applicability in observing nanostructural dynamics. This study addresses these gaps by developing a novel method that leverages a feedforward architecture with a physics-informed strategy utilizing measurement settings, enabling the reconstruction of dynamic “movies" from time-evolving diffraction images of the illuminated area. The method incorporates key enhancements, such as temporal convolution blocks to capture spatiotemporal correlations and a unified TV regularization applied to the reconstructed object, resulting in improved noise reduction and spatial smoothness. An expanded evaluation framework, including multiple metrics and systematic sensitivity analysis, is employed to comprehensively assess the method’s performance and robustness. Proof-of-concept experiments, including numerical simulations and imaging experiments of a moving Ta test chart and colloidal gold particles (dispersed in aqueous polyvinyl alcohol solutions) with synchrotron hard X-rays, validate the high imaging performance of this method. Experimental results demonstrate that structures in the sample have been successfully reconstructed at short exposure times, significantly outperforming both traditional methods and current DL-based methods. The proposed method provides efficient and reliable reconstruction of dynamic images with low computational costs, making it suitable for exploring fast-evolving phenomena in synchrotron- or free-electron laser-based applications requiring high spatiotemporal resolutions. 展开更多
关键词 coherent x ray diffraction imaging deep learning visualizing local nanostructural dynamics achieving high spatiotemporal resolutions phase retrieval observing nanostructural dynamics handling dynamic imaging managing computational costs
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