Distortion Correction for 3D Scan of Trunk Swaying Human Body Segments

We propose a method for acquiring a 3D shape of human body segments accurately. Using a light stripe triangulation range finder, we can acquire accurate 3D shape of a motionless object in dozens of seconds. If the object moves during the scanning, the acquired shape would be distorted. Naturally, humans move slightly for making balance while standing even if the subject makes an effort to stay still for avoiding the distortion in acquired shape. Our method corrects the distortion based on measured subject's motion during the scanning. Experimental results show the accuracy of the proposed method. Trunk swaying degrades the accuracy of the light stripe triangulation from 1mm to 10mm. We can keep the accuracy of as good as 2mm by applying our method

Employment and Quality of Life of Women Undergoing Assisted Reproductive Technology Treatment in Japan

聖路加国際大学修士(公衆衛生学)2022thesi

施設保育の実態に関する調査研究 (その1)

application/pdfdepartmental bulletin pape

Registration of serial sections: An evaluation method based on distortions of the ground truths

Registration of histological serial sections is a challenging task. Serial sections exhibit distortions and damage from sectioning. Missing information on how the tissue looked before cutting makes a realistic validation of 2D registrations extremely difficult. This work proposes methods for ground-truth-based evaluation of registrations. Firstly, we present a methodology to generate test data for registrations. We distort an innately registered image stack in the manner similar to the cutting distortion of serial sections. Test cases are generated from existing 3D data sets, thus the ground truth is known. Secondly, our test case generation premises evaluation of the registrations with known ground truths. Our methodology for such an evaluation technique distinguishes this work from other approaches. Both under- and over-registration become evident in our evaluations. We also survey existing validation efforts. We present a full-series evaluation across six different registration methods applied to our distorted 3D data sets of animal lungs. Our distorted and ground truth data sets are made publicly available.Comment: Supplemental data available under https://zenodo.org/record/428244

ヒカリ セツダンホウ ニ ヨル サマザマナ シセイ デ ノ サンジゲン ジンタイ ケイジョウ モデリング

京都大学0048新制・課程博士博士(情報学)甲第13199号情博第243号新制||情||51(附属図書館)UT51-2007-H472京都大学大学院情報学研究科知能情報学専攻(主査)教授 美濃 導彦, 教授 松山 隆司, 教授 中村 裕一学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA