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Physics & Imaging In Radiation Oncology

SCIE

国际简称：PHYS IMAG RADIAT ONC 参考译名：放射肿瘤学中的物理和成像

中科院分区
3区
CiteScore分区
Q1
JCR分区
Q2

基本信息：: ISSN：2405-6316; 是否OA：未开放; 是否预警：否; TOP期刊：否

出版信息：: 出版地区：Ireland; 出版商：Elsevier; 出版语言：English; 研究方向：Multiple

评价信息：: 影响因子：3.2; CiteScore指数：4.4; SJR指数：0.944; SNIP指数：0.945

发文数据：: Gold OA文章占比：100.00%; 研究类文章占比：95.94%; 年发文量：197; 自引率：0.1891...; 开源占比：0.9333; 出版撤稿占比：; 出版国人文章占比：0; OA被引用占比：

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英文简介期刊介绍 CiteScore数据中科院SCI分区 JCR分区发文数据常见问题

英文简介Physics & Imaging In Radiation Oncology期刊介绍

Physics&Imaging in Radiation Oncology is an international academic journal dedicated to the field of radiation oncology, published by Elsevier Press. This journal focuses on the application of physics and imaging techniques in radiation oncology, including dose calculation for radiation therapy, treatment planning, development of imaging techniques, and related clinical research. The journal aims to promote scientific progress in the field of radiation oncology, improve the accuracy and effectiveness of treatment.

The readership of the journal includes radiation oncologists, physicists, medical imaging experts, bioengineers, as well as scholars and graduate students engaged in related research. The magazine encourages the submission of innovative research, especially those that can significantly improve clinical practice and patient care. This journal provides a rapid peer review process to ensure that published research is of high quality and timely. In addition, as an open access journal, all articles are available for free online access, making it easy for researchers and healthcare professionals worldwide to access and disseminate knowledge.

期刊简介Physics & Imaging In Radiation Oncology期刊介绍

《Physics & Imaging In Radiation Oncology》是一本医学优秀杂志。致力于发表原创科学研究结果，并为医学各个领域的原创研究提供一个展示平台，以促进医学领域的的进步。该刊鼓励先进的、清晰的阐述，从广泛的视角提供当前感兴趣的研究主题的新见解，或审查多年来某个重要领域的所有重要发展。该期刊特色在于及时报道医学领域的最新进展和新发现新突破等。该刊近一年未被列入预警期刊名单，目前已被权威数据库SCIE收录，得到了广泛的认可。

该期刊投稿重要关注点：

预计审稿时间：6 Weeks
医学
肿瘤学
SCIE
中科院3区
非预警

Cite Score数据（2026年6月最新版）Physics & Imaging In Radiation Oncology Cite Score数据

CiteScore：4.4
SJR：0.944
SNIP：0.945

学科类别	分区	排名	百分位
大类：Physics and Astronomy 小类：Radiation	Q1	16 / 75	79%
大类：Physics and Astronomy 小类：Radiology, Nuclear Medicine and Imaging	Q2	112 / 361	69%
大类：Physics and Astronomy 小类：Oncology	Q2	194 / 428	54%

CiteScore 是由Elsevier(爱思唯尔)推出的另一种评价期刊影响力的文献计量指标。反映出一家期刊近期发表论文的年篇均引用次数。CiteScore以Scopus数据库中收集的引文为基础，针对的是前四年发表的论文的引文。CiteScore的意义在于，它可以为学术界提供一种新的、更全面、更客观地评价期刊影响力的方法，而不仅仅是通过影响因子(IF)这一单一指标来评价。

历年Cite Score趋势图

中科院SCI分区Physics & Imaging In Radiation Oncology 中科院分区

《新锐期刊分区表》（2026年3月发布） 综述期刊：否 Top期刊：否

大类学科	分区	小类学科	分区
医学	3区	ONCOLOGY 肿瘤学 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核医学	3区 3区

期刊分区表（2025年3月升级版） 综述期刊：否 Top期刊：否

大类学科	分区	小类学科	分区
医学	2区	ONCOLOGY 肿瘤学 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核医学	2区 2区

中科院分区表 是以客观数据为基础，运用科学计量学方法对国际、国内学术期刊依据影响力进行等级划分的期刊评价标准。它为我国科研、教育机构的管理人员、科研工作者提供了一份评价国际学术期刊影响力的参考数据，得到了全国各地高校、科研机构的广泛认可。

中科院分区表 将所有期刊按照一定指标划分为1区、2区、3区、4区四个层次，类似于“优、良、及格”等。最开始，这个分区只是为了方便图书管理及图书情报领域的研究和期刊评估。之后中科院分区逐步发展成为了一种评价学术期刊质量的重要工具。

历年中科院分区趋势图

JCR分区Physics & Imaging In Radiation Oncology JCR分区

2025-2026年最新版

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：ONCOLOGY	ESCI	Q2	161 / 333	51.8
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	ESCI	Q2	64 / 217	70.7
学科：ONCOLOGY	ESCI	Q2	111 / 333	66.82
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	ESCI	Q2	66 / 217	69.82

2023-2024年最新版

按JCI指标学科分区	收录子集	分区	排名	百分位
学科：ONCOLOGY	ESCI	Q2	110 / 322	66
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	ESCI	Q1	40 / 204	80.6
学科：ONCOLOGY	ESCI	Q2	88 / 322	72.83
学科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	ESCI	Q2	53 / 204	74.26

JCR分区的优势在于它可以帮助读者对学术文献质量进行评估。不同学科的文章引用量可能存在较大的差异，此时单独依靠影响因子(IF)评价期刊的质量可能是存在一定问题的。因此，JCR将期刊按照学科门类和影响因子分为不同的分区，这样读者可以根据自己的研究领域和需求选择合适的期刊。

历年影响因子趋势图

本刊中国学者近年发表论文

1、A meta-analysis of dose-volume parameters and treatment efficiency comparing O-ring and C-arm accelerator systems for craniospinal irradiation
Author: Li, Yaotao; Yang, Guozi; Lei, Liangliang; Huang, Kunhai; Liao, Yanling; Liu, Hongzhi; Tang, Ran; Gu, Anyan; Li, Yuanyuan; Bi, Suyan; Li, Zhuocheng; Wu, Yu; Pan, Zhenyu; Sun, Xingru

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2026; Vol. 38, Issue , pp. -. DOI: 10.1016/j.phro.2026.100943
2、Fuzzy masks: boosting radiomic reliability in head and neck tumors amid delineation uncertaint
Author: Cao, Jin; Zhang, Jiang; Teng, Xinzhi; Zhang, Xinyu; Lam, Saikit; Zhou, Ta; Zhang, Yuanpeng; Cai, Jing

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2026; Vol. 38, Issue , pp. -. DOI: 10.1016/j.phro.2026.100947
3、Recommendations for contouring of gross tumour volume for locally advanced lung cancer using magnetic resonance imagin
Author: Shiarli, Anna-Maria; Dubec, Michael J.; Ahmed, Merina; Asmussen, Jon T.; Bainbridge, Hannah; Belderbos, Jose S.; Brown, Sean; Bussink, Johan; Cobben, David; Geurts, Bram H. J.; Hope, Andrew; Kavanagh, John; Koh, Dow-Mu; Lalezari, Ferry; Louie, Alexander, V; Merckel, Laura G.; Hoesein, Firdaus A. M.; O'connor, James P. B.; Perez-Johnston, Rocio; Reeve, Tyson J.; Rimner, Andreas; van Rossum, Peter S. N.; Schinagl, Dominic A. X.; Schytte, Tine; Stevens, Craig; Tan, Alex; Tijssen, Rob H. N.; Tunariu, Nina; Van Herk, Marcel; Verhoeff, Joost J. C.; Wetscherek, Andreas; Wittenberg, Rianne; Woolf, David; Faivre-Finn, Corinne; McDonald, Fiona

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2026; Vol. 38, Issue , pp. -. DOI: 10.1016/j.phro.2026.100948
4、Deep learning and dual-radiomics model incorporating brachytherapy applicator type to predict radiation-induced acute rectal injury in cervical cancer patient
Author: Ning, Boda; Li, Zhengxian; Yu, Deyang; Li, Chenyu; Liu, Qi; Bai, Yanling

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2026; Vol. 37, Issue , pp. -. DOI: 10.1016/j.phro.2026.100908
5、PhysMorph: A biomechanical and image-guided deep learning framework for real-time multi-modal liver image registratio
Author: Zhang, Zeyu; Guo, Dongyang; Lu, Ke; Jiang, Zhuoran; Zhong, Hualiang; Yin, Fang-Fang; Ren, Lei; Yang, Zhenyu

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2026; Vol. 37, Issue , pp. -. DOI: 10.1016/j.phro.2026.100906
6、Potential of margin reduction for cervical cancer radiotherapy in an online adaptive image-guided workflo
Author: Li, Fanghua; Ding, Shouliang; Chen, Zhanlin; Chen, Kai; Li, Junyun; Cao, Xinping; Ye, Weijun; Ouyang, Yi; Huang, Xiaodan; Chen, Foping

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2026; Vol. 37, Issue , pp. -. DOI: 10.1016/j.phro.2026.100923
7、Contour-informed inter-patient deformable registration for more reliable voxel-based analysis of Head-and-Neck cancer patient
Author: Ruan, Xingyue; Li, Xia; Li, Muheng; Bachtiary, Barbara; Lomax, Antony; Chen, Zhiling; Zhang, Ye

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2026; Vol. 37, Issue , pp. -. DOI: 10.1016/j.phro.2025.100898
8、A physics-informed deep learning model for predicting beam dose distribution of intensity-modulated radiation therapy treatment plan
Author: Sun, Zihan; Yan, Yongheng; Chen, Yuanhua; Yao, Guorong; Wang, Jiazhou; Hu, Weigang; Lu, Zhongjie; Yan, Senxiang

Journal: PHYSICS & IMAGING IN RADIATION ONCOLOGY. 2025; Vol. 34, Issue , pp. -. DOI: 10.1016/j.phro.2025.100779