當前位置：首頁 SCI期刊 SCIE期刊醫(yī)學中科院2區(qū) JCRQ1 期刊介紹(非官網(wǎng))

Insights Into ImagingSCIE

國際簡稱：INSIGHTS IMAGING 參考譯名：洞察成像

中科院分區(qū)
2區(qū)
CiteScore分區(qū)
Q1
JCR分區(qū)
Q1

基本信息：: ISSN：1869-4101; E-ISSN：1869-4101; 是否OA：開放; 是否預(yù)警：否; TOP期刊：是

出版信息：: 出版地區(qū)：GERMANY; 出版商：Springer Berlin Heidelberg; 出版語言：English; 出版周期：1 issue/year; 出版年份：2010; 研究方向：Medicine-Radiology, Nuclear Medicine and Imaging

評價信息：: 影響因子：4.1; CiteScore指數(shù)：7.3; SJR指數(shù)：1.24; SNIP指數(shù)：2.142

發(fā)文數(shù)據(jù)：: Gold OA文章占比：99.66%; 研究類文章占比：77.40%; 年發(fā)文量：208; 自引率：0.0425...; 開源占比：0.996; 出版撤稿占比：0; 出版國人文章占比：0.02; OA被引用占比：1

投稿咨詢加急見刊

英文簡介期刊介紹 CiteScore數(shù)據(jù) 中科院SCI分區(qū) JCR分區(qū) 發(fā)文數(shù)據(jù) 常見問題

英文簡介Insights Into Imaging期刊介紹

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.

期刊簡介Insights Into Imaging期刊介紹

《Insights Into Imaging》自2010出版以來，是一本醫(yī)學優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學研究結(jié)果，并為醫(yī)學各個領(lǐng)域的原創(chuàng)研究提供一個展示平臺，以促進醫(yī)學領(lǐng)域的的進步。該刊鼓勵先進的、清晰的闡述，從廣泛的視角提供當前感興趣的研究主題的新見解，或?qū)彶槎嗄陙砟硞€重要領(lǐng)域的所有重要發(fā)展。該期刊特色在于及時報道醫(yī)學領(lǐng)域的最新進展和新發(fā)現(xiàn)新突破等。該刊近一年未被列入預(yù)警期刊名單，目前已被權(quán)威數(shù)據(jù)庫SCIE收錄，得到了廣泛的認可。

該期刊投稿重要關(guān)注點：

預(yù)計審稿時間： 13 Weeks
國際TOP期刊
醫(yī)學
RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
SCIE
中科院2區(qū)
非預(yù)警

Cite Score數(shù)據(jù)（2024年最新版）Insights Into Imaging Cite Score數(shù)據(jù)

CiteScore：7.3
SJR：1.24
SNIP：2.142

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

CiteScore 是由Elsevier(愛思唯爾)推出的另一種評價期刊影響力的文獻計量指標。反映出一家期刊近期發(fā)表論文的年篇均引用次數(shù)。CiteScore以Scopus數(shù)據(jù)庫中收集的引文為基礎(chǔ)，針對的是前四年發(fā)表的論文的引文。CiteScore的意義在于，它可以為學術(shù)界提供一種新的、更全面、更客觀地評價期刊影響力的方法，而不僅僅是通過影響因子(IF)這一單一指標來評價。

歷年Cite Score趨勢圖

中科院SCI分區(qū)Insights Into Imaging 中科院分區(qū)

中科院 2023年12月升級版 綜述期刊：否 Top期刊：否

大類學科	分區(qū)	小類學科	分區(qū)
醫(yī)學	2區(qū)	RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING 核醫(yī)學	2區(qū)

中科院分區(qū)表 是以客觀數(shù)據(jù)為基礎(chǔ)，運用科學計量學方法對國際、國內(nèi)學術(shù)期刊依據(jù)影響力進行等級劃分的期刊評價標準。它為我國科研、教育機構(gòu)的管理人員、科研工作者提供了一份評價國際學術(shù)期刊影響力的參考數(shù)據(jù)，得到了全國各地高校、科研機構(gòu)的廣泛認可。

中科院分區(qū)表 將所有期刊按照一定指標劃分為1區(qū)、2區(qū)、3區(qū)、4區(qū)四個層次，類似于“優(yōu)、良、及格”等。最開始，這個分區(qū)只是為了方便圖書管理及圖書情報領(lǐng)域的研究和期刊評估。之后中科院分區(qū)逐步發(fā)展成為了一種評價學術(shù)期刊質(zhì)量的重要工具。

歷年中科院分區(qū)趨勢圖

JCR分區(qū)Insights Into Imaging JCR分區(qū)

2023-2024 年最新版

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

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

JCR分區(qū)的優(yōu)勢在于它可以幫助讀者對學術(shù)文獻質(zhì)量進行評估。不同學科的文章引用量可能存在較大的差異，此時單獨依靠影響因子(IF)評價期刊的質(zhì)量可能是存在一定問題的。因此，JCR將期刊按照學科門類和影響因子分為不同的分區(qū)，這樣讀者可以根據(jù)自己的研究領(lǐng)域和需求選擇合適的期刊。

歷年影響因子趨勢圖

發(fā)文數(shù)據(jù)

2023-2024 年國家/地區(qū)發(fā)文量統(tǒng)計

國家/地區(qū)數(shù)量
Italy65
USA64
England38
Austria34
Spain32
France29
Netherlands28
Switzerland21
GERMANY (FED REP GER)20
Belgium19

本刊中國學者近年發(fā)表論文

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