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Medical Image Analysis (MIA)

Publisher :

Elsevier

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Computer Science
  • Computer Graphics
  • Computer-Aided Design

    • +7

e-ISSN :

1361-8423

Issue Frequency :

Quarterly

Impact Factor :

10.9

p-ISSN :

1361-8415

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 - 1361-8415, E-ISSN - 1361-8423, Established in - 1996, Impact Factor - 10.9

Not Provide Crossref DOI

Indexed in Scopus, WoS

Not indexed in DOAJ, PubMed, UGC CARE

Indexing

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Scopus
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WoS
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Elsevier

+5 More

Publications of MIA

  • dott image October, 2024

Dual-stream multi-dependency graph neural network enables precise cancer survival analysis

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...

  • dott image July, 2022

A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data

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...

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