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Journal Photo for Medical Image Analysis
Peer reviewed only Open Access

Medical Image Analysis (MIA)

Publisher : Elsevier
Computer Science Computer Graphics Computer-Aided Design
e-ISSN 1361-8423
p-ISSN 1361-8415
Issue Frequency Quarterly
Impact Factor 10.9
Est. Year 1996
Mobile 31204853767
Country India
Language English
APC YES
Impact Factor Assignee Google Scholar
Email nlinfo@sciencedirect.com

Journal Descriptions

An official journal of the MICCAI Society Medical Image Analysis provides a forum for the dissemination of new research results in the field of medical and biological image analysis, with special emphasis on efforts related to the applications of computer vision, virtual reality and robotics to biomedical imaging problems. The journal publishes the highest quality, original papers that contribute to the basic science of processing, analysing and utilizing medical and biological images for these purposes. The journal is interested in approaches that utilize biomedical image datasets at all spatial scales, ranging from molecular/cellular imaging to tissue/organ imaging. While not limited to these alone, the typical biomedical image datasets of interest include those acquired from: Magnetic resonance Ultrasound Computed tomography Nuclear medicine X-ray

Medical Image Analysis (MIA) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Computer Science, Computer Graphics, Computer-Aided Design, Radiology, Nuclear Medicine, Radiological, Health Professions, Ultrasound Technology, Health Informatics, Pattern Recognition , Online or Print , Quarterly Journal

  • UGC Approved, ISSN Approved: P-ISSN P-ISSN: 1361-8415, E-ISSN: 1361-8423, Established: 1996, Impact Factor: 10.9
  • Does Not Provide Crossref DOI
  • Indexed in: Scopus, WoS

  • Not indexed in DOAJ, PubMed, UGC CARE

Indexing

Publications of MIA

Pietro Liò October, 2024
Histopathology image-based survival prediction aims to provide a precise assessment of cancer prognosis and can inform personalized treatment decision-making in order to improve patient outc...
Pietro Liò July, 2022
Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully employed to understand the organisation of the human brain. Typically, the brain is parcellated into regio...