Impact Factor
3.86
Journal Citation Impact
Estimated influence, citation density, publishing volume, and citation integrity from the analytics table.
Citation rate
4.41
1,930 total citations
h5-index
28
h5 depth signal
Cited share
80.4%
364 of 453
Total citations
1,930
Citation footprint
Metric signal
4.89
External metric anchor
Self-citation
4.3%
83 self-citations
Citations Trend
Monthly Publications Cadence
Citing Geographic Demographics
China
501
United States
354
Turkey
123
South Korea
77
India
74
Citing Fields of Research
AI & Machine Learning
543
Computer Vision & Graphics
543
Brain Imaging
271
Biomedical Physics
267
Lung Cancer
114
Publishing Activity & Reach
Volume, recency, access pattern, and citing-community signals from the journal analytics record.
All-time article footprint
1,464
Articles tracked across the journal lifetime
Indexed publication set
453
364 cited publications
Last 12 months
626
52.2 publications/month
Open access share
24.6%
154 OA publications in the last year
Leading citing country
China
501 citing publications
Leading citing field
AI & Machine Learning
543 citing publications
Latest tracked publication
16 October 2026
10 recent records available
Coverage & Indexing History
v37n1, 2024-
v37n1, 2024-
Active Coverage
Research Focus & Classification
Indexed Subjects
Computer Vision & Graphics
AI & Machine Learning
Biomedical Physics
Brain Imaging
Lung Cancer
Musculoskeletal Disorders
Issuing & Sponsoring Bodies
sponsoring body
Society for Imaging Informatics in Medicine
Broad Categories
Diagnostic Imaging
Medical Informatics
Radiology
Computer Vision & Graphics
Biomedical Physics
Brain Imaging
Musculoskeletal Disorders
Lung Cancer
Breast Cancer
MeSH Descriptors
Diagnostic Imaging
Medical Informatics
Radiology Information Systems
Latest Publications
Recent article records with DOI-first linking and condensed abstracts.
01
DOI 10.1007/s10278-026-02408-x
Open DOI
A Survey of Computational Color Constancy: Approaches and Emerging Applications in Medical Imaging
As the evening sets in and natural light fades to artificial light, it is remarkable how the colors around us still appear nearly the same. This phenomenon, known as color constancy, allows us to perceive relatively stable colors even as...
02
DOI 10.1007/s10278-026-02365-5
Open DOI
An Accountable Encounter-Based Imaging Workflow for Point-of-Care Ultrasound: Integrating Image Availability, Clinician Attribution, and Documentation Accountability
Point-of-care ultrasound (POCUS) is integral to emergency department (ED) care, but traditional order-based imaging workflows (OBIWs) are poorly aligned with unscheduled encounters and dynamic bedside imaging needs. We describe an accoun...
03
DOI 10.1007/s10278-026-02402-3
Open DOI
Investigation on Automatic Classification of Bone, Lymph Node, and Local Lesions in CT Images of Prostate Cancer Patients
Accurate assessment of different types of prostate cancer (PCa) lesions is a crucial part of treatment planning. Following a computed tomography (CT) or a positron emission tomography (PET)/CT imaging scan, a significant amount of time i...
04
DOI 10.1007/s10278-026-02368-2
Open DOI
Evaluating Explicit Anatomical Priors Beyond a Mature CT Detector for Six Acute Abdominal Emergencies
To test whether anatomical priors from a general-purpose organ segmentation model (TotalSegmentator, TS), applied at inference or during training, improve an externally validated YOLOv11 detector for six acute abdominal emergencies. The ...
05
DOI 10.1007/s10278-026-02203-8
Open DOI
Diagnosis of Suspected Pituitary Microadenomas: The Complementary Role of Habitat-based Non-enhanced MRI Radiomics Features
To develop and validate a combined model for detecting pituitary microadenomas in suspected cases using non-contrast T1-weighted sagittal (T1SAG) magnetic resonance imaging (MRI), and to assess its performance as a non-contrast imaging-b...
06
DOI 10.1007/s10278-026-02363-7
Open DOI
Automated Segmentation of Wound Bed Tissue from Clinical Photographs: A Benchmark of Five Deep Learning Architectures Under a Shared Protocol
Accurate characterisation of the wound bed, the relative proportions of granulation, slough and necrotic tissue described by the red–yellow–black model, is central to monitoring healing and guiding debridement in chronic-wound care, yet ...
07
DOI 10.1007/s10278-026-02403-2
Open DOI
Building and Validating a Data-Governance Workflow for Artificial Intelligence–Based Tuberculosis Detection from Chest Radiographs, and Quantifying the Impact of Data Leakage
Studies applying artificial intelligence (AI) to tuberculosis (TB) detection from chest radiographs (CXR) focus on models and metrics, yet the quality, provenance and reproducibility of the data workflow decide the reliability of results...
08
09
10
Bibliographical & Catalog Notes
Also issued in print.
"Official peer-reviewed journal of the Society for Imaging Informatics in Medicine (SIIM)."