About the Journal

ABOUT INTERNATIONAL JOURNAL OF BIOMEDICAL IMAGE INTELLIGENCE

The International Journal of Biomedical Image Intelligence (IJBII) is an international, peer-reviewed, open-access scholarly journal published by Prime Crest Publishers.

IJBII is dedicated to advancing research at the intersection of biomedical imaging and artificial intelligence. The journal provides a specialized platform for research involving intelligent methods for acquiring, processing, analyzing, interpreting and understanding biomedical and medical images.

Advances in artificial intelligence, machine learning, deep learning and computer vision are transforming biomedical imaging and creating new possibilities for disease detection, image segmentation, computer-aided diagnosis, medical visualization, clinical decision support and personalized healthcare.

IJBII provides an interdisciplinary forum for researchers, academics, clinicians, engineers and healthcare technology professionals to advance these developments through rigorous scientific research.

Our Purpose

The purpose of IJBII is to promote high-quality research that advances the scientific and practical foundations of intelligent biomedical image analysis.

The journal encourages research that combines innovative computational methods with meaningful biomedical, clinical and healthcare applications.

Aims and Objectives

IJBII aims to:

  1. Promote high-quality research in biomedical image intelligence.
  2. Advance the application of artificial intelligence and machine learning to medical and biomedical imaging.
  3. Encourage innovation in medical image processing, analysis and interpretation.
  4. Promote interdisciplinary collaboration among computer scientists, engineers, biomedical researchers, clinicians and healthcare professionals.
  5. Support the development and validation of reliable and clinically relevant intelligent imaging systems.
  6. Encourage research in explainable, trustworthy and responsible artificial intelligence for healthcare.
  7. Provide a scholarly platform for emerging computational approaches to biomedical imaging.
  8. Promote transparent, reproducible and scientifically rigorous research.
  9. Encourage the development and evaluation of intelligent tools for medical diagnosis and clinical decision support.
  10. Contribute to the advancement of intelligent healthcare technologies.

Scope of the Journal

IJBII covers research at the intersection of biomedical imaging, artificial intelligence and computational intelligence.

Core areas include:

  • Biomedical and medical imaging
  • Artificial intelligence and machine learning
  • Medical image analysis and computer vision
  • Image reconstruction, segmentation, registration and classification
  • Radiomics and quantitative imaging
  • Digital pathology and microscopy
  • Computer-aided diagnosis
  • Multimodal biomedical imaging
  • Biomedical imaging datasets and benchmarks
  • Explainable and trustworthy biomedical AI
  • Biomedical informatics
  • Clinical decision-support technologies
  • Intelligent healthcare systems

Imaging modalities and applications may include MRI, CT, X-ray, ultrasound, PET, SPECT, nuclear medicine imaging, histopathology, microscopy, retinal imaging, dermatological imaging, molecular imaging and other biomedical imaging technologies.

The journal welcomes methodological, computational, translational and clinically relevant research. Detailed subject coverage is provided in the journal's Focus and Scope.

Interdisciplinary Approach

IJBII recognizes that meaningful advances in biomedical image intelligence require collaboration across multiple disciplines.

The journal therefore encourages contributions spanning:

  • Computer science
  • Artificial intelligence and machine learning
  • Computer vision
  • Biomedical engineering
  • Electrical and electronic engineering
  • Medical imaging and radiology
  • Medicine and biomedical sciences
  • Data science
  • Mathematics and statistics
  • Neuroscience
  • Healthcare and biomedical informatics

International Perspective

IJBII provides an international platform for researchers to exchange knowledge, methodologies and innovations in biomedical image intelligence.

The journal welcomes contributions from all geographical regions, including international collaborations, multicentre studies and research addressing biomedical imaging challenges across diverse healthcare environments.

Target Audience

IJBII serves:

  • Artificial intelligence and machine learning researchers
  • Computer vision researchers
  • Computer scientists and data scientists
  • Biomedical engineers
  • Medical imaging specialists
  • Radiologists and clinicians
  • Medical and biomedical researchers
  • Healthcare and biomedical informatics researchers
  • University academics and postgraduate researchers
  • Healthcare technology professionals

Research Integrity

IJBII is committed to rigorous, transparent and responsible scholarly publishing. Authors are expected to comply with applicable standards concerning research ethics, patient privacy, authorship, competing interests, data integrity, originality and responsible use of artificial intelligence.

Detailed requirements are provided in the journal's Publishing Ethics Statement, Peer Review Process, Generative AI Policy, Plagiarism Policy and related publication policies.

Our Vision

To become a respected international scholarly journal advancing intelligent biomedical imaging and artificial intelligence for improved healthcare and scientific discovery.

Our Mission

To promote rigorous, innovative and interdisciplinary research that advances biomedical image intelligence, develops reliable artificial intelligence technologies and supports better medical research, diagnosis and healthcare decision-making.

Publisher

Prime Crest Publishers

Prime Crest Publishers supports scholarly communication by providing researchers and academic communities with professional platforms for disseminating high-quality research.

IJBII forms part of Prime Crest Publishers' portfolio of specialized scholarly journals supporting research across emerging and interdisciplinary fields.

Commitment to Innovation

IJBII is committed to addressing the rapidly evolving landscape of intelligent biomedical imaging while maintaining scientific rigour, clinical relevance, transparency and responsible innovation.

The journal welcomes emerging approaches involving artificial intelligence, deep learning, computer vision, multimodal imaging, foundation models, explainable AI, generative AI and other computational technologies where they make a meaningful contribution to biomedical imaging or healthcare.

INTERNATIONAL JOURNAL OF BIOMEDICAL IMAGE INTELLIGENCE

IJBII

Advancing Biomedical Imaging Through Intelligent Analysis

FOCUS AND SCOPE

The International Journal of Biomedical Image Intelligence (IJBII) publishes original, high-quality research at the intersection of biomedical imaging, artificial intelligence, machine learning, computer vision and intelligent healthcare technologies.

The journal focuses on computational and intelligent methods for the acquisition, reconstruction, processing, analysis, interpretation and clinical application of biomedical and medical images.

IJBII welcomes methodological, technical, translational and clinically relevant studies that demonstrate clear scientific contribution, appropriate validation and meaningful relevance to biomedical imaging or healthcare.

Core Areas of Interest

Biomedical and Medical Imaging

IJBII welcomes research involving imaging modalities including:

  • Magnetic Resonance Imaging (MRI)
  • Computed Tomography (CT)
  • X-ray imaging
  • Ultrasound imaging
  • Positron Emission Tomography (PET)
  • Single-Photon Emission Computed Tomography (SPECT)
  • Nuclear medicine imaging
  • Histopathology
  • Digital pathology
  • Microscopy
  • Retinal imaging
  • Dermatological imaging
  • Molecular imaging
  • Multimodal biomedical imaging

Artificial Intelligence and Machine Learning

Relevant computational approaches include:

  • Machine learning
  • Deep learning
  • Neural networks
  • Convolutional neural networks
  • Vision transformers
  • Foundation models
  • Generative artificial intelligence
  • Self-supervised learning
  • Semi-supervised learning
  • Transfer learning
  • Federated learning
  • Reinforcement learning
  • Multimodal AI
  • Explainable artificial intelligence
  • Interpretable machine learning

Medical Image Analysis and Computer Vision

The journal welcomes research involving:

  • Image enhancement
  • Image reconstruction
  • Image restoration
  • Image denoising
  • Image segmentation
  • Image registration
  • Image classification
  • Object detection
  • Feature extraction
  • Image fusion
  • Image representation
  • Image compression
  • 3D and volumetric image analysis
  • Medical image visualization
  • Quantitative image analysis

Radiomics and Quantitative Imaging

Relevant areas include:

  • Radiomics
  • Imaging biomarkers
  • Quantitative imaging
  • Feature engineering
  • Image-based prediction
  • Prognostic modelling
  • Treatment response assessment
  • Imaging-genomics and multimodal data integration

Computer-Aided Diagnosis and Clinical Decision Support

IJBII welcomes intelligent imaging systems addressing:

  • Disease detection
  • Disease classification
  • Cancer diagnosis
  • Tumour detection
  • Lesion analysis
  • Abnormality detection
  • Screening
  • Risk prediction
  • Prognosis
  • Treatment planning
  • Clinical decision support
  • Precision and personalized healthcare

Digital Pathology and Microscopy

Relevant topics include:

  • Histopathological image analysis
  • Computational pathology
  • Cell and tissue segmentation
  • Microscopy image analysis
  • Digital slide analysis
  • Automated grading and classification
  • AI-assisted pathological diagnosis

Explainable, Trustworthy and Responsible Biomedical AI

IJBII particularly encourages research addressing:

  • Explainable AI
  • Model interpretability
  • Model transparency
  • Algorithmic fairness
  • Bias detection and mitigation
  • Model robustness
  • Model uncertainty
  • AI safety
  • Human-AI interaction
  • Clinical validation
  • Responsible deployment of medical AI
  • Ethical and trustworthy AI in healthcare

Biomedical Imaging Data, Datasets and Benchmarks

The journal welcomes studies addressing:

  • Biomedical imaging datasets
  • Medical imaging benchmarks
  • Dataset development
  • Dataset curation
  • Image annotation
  • Data augmentation
  • Synthetic medical images
  • Generative models
  • Data quality
  • Class imbalance
  • Cross-dataset evaluation
  • External validation
  • Benchmarking studies
  • Reproducible computational research

Biomedical Informatics and Intelligent Healthcare

Relevant areas include:

  • Biomedical informatics
  • Health informatics
  • Clinical informatics
  • Multimodal clinical data integration
  • AI-assisted healthcare systems
  • Intelligent diagnostic systems
  • Medical decision-support technologies
  • Computational approaches integrating imaging with clinical, genomic or laboratory data

Clinical Application Areas

IJBII welcomes biomedical imaging research applied to areas including:

  • Neurology and neuroscience
  • Oncology
  • Cardiology
  • Pulmonology
  • Ophthalmology
  • Dermatology
  • Orthopaedics
  • Radiology
  • Pathology
  • Gastroenterology
  • Obstetrics and gynaecology
  • Paediatrics
  • Infectious diseases
  • Public health and population imaging

Interdisciplinary Research

The journal encourages interdisciplinary contributions involving combinations of:

  • Computer science
  • Artificial intelligence
  • Machine learning
  • Computer vision
  • Biomedical engineering
  • Electrical and electronic engineering
  • Medical imaging
  • Radiology
  • Medicine
  • Biomedical sciences
  • Data science
  • Mathematics and statistics
  • Neuroscience
  • Healthcare informatics

Research Expectations

Submissions should demonstrate a clear scientific contribution and appropriate methodological rigour.

Studies involving artificial intelligence or machine learning should, where applicable, provide sufficient information on datasets, training procedures, validation methods, evaluation metrics, potential bias, limitations and reproducibility.

Clinical studies should demonstrate appropriate ethical compliance and clearly explain the clinical relevance of the work.

Out of Scope

IJBII generally does not consider manuscripts that:

  • Use artificial intelligence or machine learning without a meaningful biomedical imaging, biomedical data or healthcare application.
  • Present only routine application of established algorithms without a clear scientific, methodological or clinical contribution.
  • Lack adequate experimental validation or appropriate comparison with relevant methods.
  • Focus exclusively on non-biomedical image processing.
  • Present purely theoretical AI or computer vision research without a meaningful biomedical or healthcare connection.
  • Present clinical case material without sufficient scientific, imaging or computational relevance.
  • Lack appropriate ethical approval, consent or privacy safeguards where these are required.
  • Rely on fabricated, manipulated or inadequately documented data.
  • Make unsupported clinical claims or conclusions beyond the evidence presented.

International Scope

IJBII welcomes submissions from researchers worldwide and encourages international collaboration, multicentre studies and research addressing biomedical imaging challenges across diverse populations, healthcare systems and resource settings.