Computerized Medical Imaging And Graphics

雜志介紹

Computerized Medical Imaging And Graphics雜志介紹

《Computerized Medical Imaging And Graphics》是一本以English為主的未開放獲取國際優秀期刊，中文名稱計算機化醫學成像和圖形，本刊主要出版、報道醫學-ENGINEERING, BIOMEDICAL領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為5.4，最新CiteScore 指數為10.7。

本刊近期中國學者發表的論文主要有：

• Does perfect filtering really guarantee perfect phase correction for diffusion MRI data?

  Author: Liu, Feihong; Yang, Junwei; Feng, Mingyue; Cui, Zhiming; He, Xiaowei; Zhou, Luping; Feng, Jun; Shen, Dinggang

• C2BA-UNet: A context-coordination multi-atlas boundary-aware UNet-like method for PET/CT images based tumor segmentation

  Author: Luo, Shijie; Jiang, Huiyan; Wang, Meng

• SGLSA: Sphygmus gated laser speckle angiography for microcirculation hemodynamics imaging

  Author: Feng, Ximeng; Geng, Mufeng; Meng, Xiangxi; Zou, Da; Jin, Zi; Liu, Gangjun; Zhou, Chuanqing; Ren, Qiushi; Lu, Yanye

• Anatomical attention-based prediction of postoperative pulmonary venous obstruction via CTA images

  Author: Pei, Yuchen; Shi, Guocheng; Li, Jieyu; Sun, Dazhen; Wen, Chen; Li, Jiang; Huang, Meiping; Chen, Huiwen; Wang, Lisheng

英文介紹

Computerized Medical Imaging And Graphics雜志英文介紹

The purpose of the journal Computerized Medical Imaging and Graphics is to act as a source for the exchange of research results concerning algorithmic advances, development, and application of digital imaging in disease detection, diagnosis, intervention, prevention, precision medicine, and population health. Included in the journal will be articles on novel computerized imaging or visualization techniques, including artificial intelligence and machine learning, augmented reality for surgical planning and guidance, big biomedical data visualization, computer-aided diagnosis, computerized-robotic surgery, image-guided therapy, imaging scanning and reconstruction, mobile and tele-imaging, radiomics, and imaging integration and modeling with other information relevant to digital health. The types of biomedical imaging include: magnetic resonance, computed tomography, ultrasound, nuclear medicine, X-ray, microwave, optical and multi-photon microscopy, video and sensory imaging, and the convergence of biomedical images with other non-imaging datasets.