Books

Reports

1.

Junji Morishita, Yasuyuki Ueda, New solutions for automated image recognition and identification: challenges to radiographic technology and forensic pathology, Radiological Physics and Technology, 10.1007/s12194-021-00611-9, Radiological Physics and Technology, 14(2), 123-133 , 2021.03, This paper outlines the history of biometrics for personal identification, the current status of the initial biological fingerprint techniques for digital chest radiography, and patient verification during medical imaging, such as computed tomography and magnetic resonance imaging. Automated image recognition and identification developed for clinical images without metadata could also be applied to the identification of victims in mass disasters or other unidentified individuals. The development of methods that are adaptive to a wide range of recent imaging modalities in the fields of radiologic technology, patient safety, forensic pathology, and forensic odontology is still in its early stages. However, its importance in practice will continue to increase in the future..

Papers

1.	Koji OURA, Noriaki IKEDA, Yongsu YOON, Toyoyuki KATO, Junji MORISHITA, Potential for personal identification using the volume of the mastoid air cells extracted from post mortem computed tomographic images, Legal Medicine, 10.1016/j.legalmed.2022.102060, 58, 2022.04, This study revealed the usefulness of volumetric analysis of mastoid air cells (MACs) extracted from postmortem computed tomography (PMCT) images in characterizing individuals. To characterize deceased persons, the MACs volumes of 61 Japanese PMCT images were measured after thresholding in Hounsfield units and based on the number of voxels on the right and left sides and the voxel size for each person. The volume differences between the right and left MACs and sex were examined. Although there were no obvious volume differences between males and females, the order of sizes on the two sides varied for each person. Moreover, deceased persons could be roughly classified using the total volume of MACs. Deceased persons with similar total volumes could be distinguished further by comparing the ratio of volumes in bilateral MACs. Although the identification process is dependent on samples and different sizes of bilateral MACs, our pilot study indicated that 81.9% (50/61) of deceased persons could be distinguished. In conclusion, volumetric analysis of MACs measured using PMCT imaging has the potential to identify individuals and reduce the number of candidates..
2.	Junji Morishita1and Yasuyuki Ueda, New solutions for automated image recognition and identification: challenges to radiologic technology and forensic pathlogy, Radiological Physics and Technology (RPT), 10.1007/s12194-021-00611-9, 14, 2, 123-133, 2021.06, This paper outlines the history of biometrics for personal identification, the current status of the initial biological fingerprint techniques for digital chest radiography, and patient verification during medical imaging, such as computed tomography and magnetic resonance imaging. Automated image recognition and identification developed for clinical images without metadata could also be applied to the identification of victims in mass disasters or other unidentified individuals. The development of methods that are adaptive to a wide range of recent imaging modalities in the fields of radiologic technology, patient safety, forensic pathology, and forensic odontology is still in its early stages. However, its importance in practice will continue to increase in the future..
3.	Junji Morishita, Kiyoshi Dogomori, Shiro Hatanaka, Takeshi Hiwasa, Yasuhiko Nakamura, Noriyuki Hashimoto, Yoshiharu Higashida, Fukai Toyofuku, Masafumi Ohki, Effect of test patterns on measurement of the luminance of LCD devices by use of a telescopic-type luminance meter, Radiological Physics and Technology, Vol.1 　　　　　　　　　　　p.95-p.99, 2008.01.
4.	Junji Morishita, Hideyuki Watanabe, Shigehiko Katsuragawa,Nobuhiro Oda, Yoshiharu Sukenobu, Hiroko Okazaki, Hajime Nakata, Kunio Doi, Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors for chest radiographs, Academic Radilogy, 10.1016/j.acra.2004.11.008, 12, 1, 97-103, Vol.12 No.1 PP97-103, 2005.01.
5.	Junji Morishita, Shigehiko Katsuragawa,Yasuo Sasaki, Kunio Doi, Potential usefulness of biological fingerprints in chest radiographs for automated patient recognition and identification, Academic Radiology, Vol.11 No.3 PP.309-315, 2004.03.
6.	Junji Morishita，Kunio Doi，Shigehiko Katsuragawa，Laurence Moninier-Cholley，and Heber MacMahon, Computer-aided diagnosis for interstitial infiltrates in chest radiographs: optical-density dependence of texture measures, Medical Physics, Vol.22 No.9 p.1515-p.1522, 1995.09.
7.	＠Junji Morishita，Kunio Doi，Romain Bollen， Philip C. Bunch，Dietmar Hoeschen， Gerard　Sirand-rey,and Yoshiharu Sukenobu, Comparison of two methods for accurate measurement of modulation transfer functions of screen-film systems, Medical Physics, Vol.22 No.2 p.193-p.200, 1995.02.

Presentations

1.	Development of an automated search method to find lost images in PACS environment by use of biological fingerprints and image-matching technique.

Image engineering (School of health sciences) Apr.2004-
Image processing (Dept. of Health Sciences, School of Medicine) Oct.2004-
Equipment for radioisotope examination (Dept. of Health Sciences, School of Medicine) Apr.2005-
Equipment for diagnostic imaging (Dept. of Health Sciences, School of Medicine) Apr.2005-
Computer-aided diagnosis (Dept. of Health Sciences, School of Medicine) Apr.2006-2010
Health Science Research (Dept. of Health Sciences, Graduate School of Medical Sciences) Apr.2007-
Medical Image Sciences (Dept. of Health Sciences, Graduate School of Medical Sciences) Apr. 2007-
Radiographic technique 2 (Dept. of Health Sciences, School of Medicine) 2010-

A lecturer of an extension of Dept. of Health Sciences, School of Medicine, Kyushu University for 2004 (July 10, 2004)..