Insights Into Imaging SCIE

國際簡稱：INSIGHTS IMAGING 參考譯名：洞察成像

主要研究方向：Medicine-Radiology, Nuclear Medicine and Imaging 非預(yù)警期刊審稿周期： 13 Weeks

《洞察成像》(Insights Into Imaging)是一本由Springer Berlin Heidelberg出版的以Medicine-Radiology, Nuclear Medicine and Imaging為研究特色的國際期刊，發(fā)表該領(lǐng)域相關(guān)的原創(chuàng)研究文章、評論文章和綜述文章，及時報道該領(lǐng)域相關(guān)理論、實(shí)踐和應(yīng)用學(xué)科的最新發(fā)現(xiàn)，旨在促進(jìn)該學(xué)科領(lǐng)域科學(xué)信息的快速交流。該期刊是一本開放期刊，近三年沒有被列入預(yù)警名單。該期刊享有很高的科學(xué)聲譽(yù)，影響因子不斷增加，發(fā)行量也同樣高。

2區(qū) 中科院分區(qū)
Q1 JCR分區(qū)
208 年發(fā)文量
4.1 IF影響因子
開放是否OA
2010 創(chuàng)刊年份
1 issue/year 出版周期
English 出版語言

Insights into Imaging (I3) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere!

I3 continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe.

Founded by the European Society of Radiology (ESR), I3 creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy.

A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I3 an indispensable source for current information in this field.

I3 is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly.

The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members.

The journal went open access in 2012, which means that all articles published since then are freely available online.

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Insights Into Imaging期刊信息

ISSN：1869-4101
出版語言：English
是否OA：開放
E-ISSN：1869-4101
出版地區(qū)：GERMANY
是否預(yù)警：否
出版商：Springer Berlin Heidelberg
出版周期：1 issue/year
創(chuàng)刊時間：2010
開源占比：0.996
Gold OA文章占比：99.66%
OA被引用占比：1
出版國人文章占比：0.02
出版撤稿占比：0
研究類文章占比：77.40%

Insights Into Imaging CiteScore評價數(shù)據(jù)（2024年最新版）

CiteScore

SJR

SNIP

CiteScore 指數(shù)

7.3

1.24

2.142

學(xué)科類別	分區(qū)	排名	百分位
大類：Medicine 小類：Radiology, Nuclear Medicine and Imaging	Q1	42 / 333	87%

名詞解釋：CiteScore 是衡量期刊所發(fā)表文獻(xiàn)的平均受引用次數(shù)，是在 Scopus 中衡量期刊影響力的另一個指標(biāo)。當(dāng)年CiteScore 的計(jì)算依據(jù)是期刊最近4年（含計(jì)算年度）的被引次數(shù)除以該期刊近四年發(fā)表的文獻(xiàn)數(shù)。例如，2022年的 CiteScore 計(jì)算方法為：2022年的 CiteScore =2019-2022年收到的對2019-2022年發(fā)表的文件的引用數(shù)量÷2019-2022年發(fā)布的文獻(xiàn)數(shù)量注：文獻(xiàn)類型包括：文章、評論、會議論文、書籍章節(jié)和數(shù)據(jù)論文。

Insights Into Imaging中科院評價數(shù)據(jù)

中科院 2023年12月升級版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	醫(yī)學(xué)	2區(qū)	RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核醫(yī)學(xué)	2區(qū)

中科院 2022年12月升級版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	醫(yī)學(xué)	2區(qū)	RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核醫(yī)學(xué)	2區(qū)

中科院 2021年12月舊的升級版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	醫(yī)學(xué)	3區(qū)	RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核醫(yī)學(xué)	3區(qū)

中科院 2021年12月基礎(chǔ)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	醫(yī)學(xué)	2區(qū)	RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核醫(yī)學(xué)	2區(qū)

中科院 2021年12月升級版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	醫(yī)學(xué)	3區(qū)	RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核醫(yī)學(xué)	3區(qū)

中科院 2020年12月舊的升級版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	醫(yī)學(xué)	3區(qū)	RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核醫(yī)學(xué)	3區(qū)

Insights Into Imaging JCR評價數(shù)據(jù)（2023-2024年最新版）

按JIF指標(biāo)學(xué)科分區(qū)	收錄子集	分區(qū)	排名	百分位
學(xué)科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	SCIE	Q1	30 / 204	85.5%

按JCI指標(biāo)學(xué)科分區(qū)	收錄子集	分區(qū)	排名	百分位
學(xué)科：RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING	SCIE	Q1	30 / 204	85.54%

Insights Into Imaging歷年數(shù)據(jù)統(tǒng)計(jì)

影響因子

中科院分區(qū)

Insights Into Imaging中國學(xué)者發(fā)文選摘

1、Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors
Author: Jan, Ya-Ting; Tsai, Pei-Shan; Huang, Wen-Hui; Chou, Ling-Ying; Huang, Shih-Chieh; Wang, Jing-Zhe; Lu, Pei-Hsuan; Lin, Dao-Chen; Yen, Chun-Sheng; Teng, Ju-Ping; Mok, Greta S. P.; Shih, Cheng-Ting; Wu, Tung-Hsin

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-023-01412-x
2、Multi-channel deep learning model-based myocardial spatial-temporal morphology feature on cardiac MRI cine images diagnoses the cause of LVH
Author: Diao, Kaiyue; Liang, Hong-qing; Yin, Hong-kun; Yuan, Ming-jing; Gu, Min; Yu, Peng-xin; He, Sen; Sun, Jiayu; Song, Bin; Li, Kang; He, Yong

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-023-01401-0
3、CT and MRI features of hepatic epithelioid haemangioendothelioma: a multi-institutional retrospective analysis of 15 cases and a literature review
Author: Luo, Lianmei; Cai, Zeyu; Zeng, Sihui; Wang, Lizhu; Kang, Zhuang; Yang, Ning; Zhang, Yaqin

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-022-01344-y
4、Predicting histologic differentiation of solitary hepatocellular carcinoma up to 5 cm on gadoxetate disodium-enhanced MRI
Author: Yang, Ting; Wei, Hong; Wu, Yuanan; Qin, Yun; Chen, Jie; Jiang, Hanyu; Song, Bin

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-022-01354-w
5、Predictive models and early postoperative recurrence evaluation for hepatocellular carcinoma based on gadoxetic acid-enhanced MR imaging
Author: Li, Qian; Wei, Yi; Zhang, Tong; Che, Feng; Yao, Shan; Wang, Cong; Shi, Dandan; Tang, Hehan; Song, Bin

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-022-01359-5
6、Impact of glycemic control on biventricular function in patients with type 2 diabetes mellitus: a cardiac magnetic resonance tissue tracking study
Author: Zhu, Jing; Li, Wenjia; Chen, Fang; Xie, Zhen; Zhuo, Kaimin; Huang, Ruijue

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-022-01357-7
7、Deep learning and radiomic feature-based blending ensemble classifier for malignancy risk prediction in cystic renal lesions
Author: He, Quan-Hao; Feng, Jia-Jun; Lv, Fa-Jin; Jiang, Qing; Xiao, Ming-Zhao

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-022-01349-7
8、A feasibility study of reduced full-of-view synthetic high-b-value diffusion-weighted imaging in uterine tumors
Author: Tang, Qian; Zhou, Qiqi; Chen, Wen; Sang, Ling; Xing, Yu; Liu, Chao; Wang, Kejun; Liu, Weiyin Vivian; Xu, Lin

Journal: INSIGHTS INTO IMAGING. 2023; Vol. 14, Issue 1, pp. -. DOI: 10.1186/s13244-022-01350-0