Radiological Physics and Technology

Radiological Physics and Technology
影响因子:
1.7
ISSN:
print: 1865-0333
on-line: 1865-0341
研究领域:
RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
自引率:
12.50%
Gold OA文章占比:
1.86%
原创研究文献占比:
90.70%
SCI收录类型:
Emerging Sources Citation Index (ESCI) || Scopus (CiteScore)
期刊介绍英文:
The purpose of the journal Radiological Physics and Technology is to provide a forum for sharing new knowledge related to research and development in radiological science and technology, including medical physics and radiological technology in diagnostic radiology, nuclear medicine, and radiation therapy among many other radiological disciplines, as well as to contribute to progress and improvement in medical practice and patient health care.
CiteScore:
CiteScoreSJRSNIPCiteScore排名
3.00.4390.835
学科
排名
百分位
大类:Health Professions
小类:Physical Therapy, Sports Therapy and Rehabilitation
97 / 247
60%
大类:Physics and Astronomy
小类:Radiation
28 / 58
52%
大类:Medicine
小类:Radiology, Nuclear Medicine and Imaging
171 / 333
48%
发文信息
WOS期刊分区
学科分类
Q3RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
历年影响因子
2022年1.6000
2023年1.7000
历年发表
2012年52
2013年56
2014年178
2015年38
2016年46
2017年52
2018年57
2019年56
2020年46
2021年49
2022年40
投稿信息
出版周期:
4 issues per year
出版国家(地区):
Germany
初审时长:
7 days
出版商:
Springer Nature

Radiological Physics and Technology - 最新文献

Assessing knowledge about medical physics in language-generative AI with large language model: using the medical physicist exam.

Pub Date : 2024-12-01 DOI: 10.1007/s12194-024-00838-2 Noriyuki Kadoya, Kazuhiro Arai, Shohei Tanaka, Yuto Kimura, Ryota Tozuka, Keisuke Yasui, Naoki Hayashi, Yoshiyuki Katsuta, Haruna Takahashi, Koki Inoue, Keiichi Jingu

Evaluation of calculation accuracy and computation time in a commercial treatment planning system for accelerator-based boron neutron capture therapy.

Pub Date : 2024-12-01 DOI: 10.1007/s12194-024-00833-7 Akihiko Takeuchi, Katsumi Hirose, Ryohei Kato, Shinya Komori, Mariko Sato, Tomoaki Motoyanagi, Yuhei Yamazaki, Yuki Narita, Yoshihiro Takai, Takahiro Kato

Effect of deep learning reconstruction on the assessment of pancreatic cystic lesions using computed tomography.

Pub Date : 2024-12-01 DOI: 10.1007/s12194-024-00834-6 Jun Kanzawa, Koichiro Yasaka, Yuji Ohizumi, Yuichi Morita, Mariko Kurokawa, Osamu Abe
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