Computerized Medical Imaging and Graphics publishes pioneering research addressing complex computational and visualization challenges in medical imaging, including machine learning, computer vision, foundation models, generative AI and simulation, medical robotics, agentic AI, virtual and augmented reality, and quantum computing—fields that are transforming medical imaging and biomedical data science. The journal emphasizes algorithmic advances, novel methodologies and clinically oriented applications that drive disease screening, early detection, precision diagnosis, therapeutic intervention, prevention, monitoring, and telemedicine. Serving as a leading interdisciplinary platform for computing researchers, imaging scientists, engineers, and physicians, CMIG highlights AI-enabled imaging solutions that bridge methodological innovation with clinical translation.

We welcome contributions on AI-driven and emerging computational methods for image acquisition, reconstruction, visualization, analysis, and interpretation, with particular focus on deep learning, generative AI, and agentic AI that enhance diagnostic accuracy, improve therapeutic efficacy, and enable precision medicine and minimally invasive interventions. Topics of interest include novel imaging and visualization techniques; AI and machine learning; augmented and virtual reality for surgery and therapy; computer-aided diagnosis; robotic and image-guided intervention; biomedical data fusion and visualization; autonomous agents; mobile and tele-imaging; and integration of imaging with genomic, transcriptomic, proteomic, video, and audio data.

The journal covers a wide spectrum of modalities—MRI, CT, ultrasound, nuclear medicine, X-ray, microwave, endoscopy, digital pathology, optical and multiphoton microscopy, spatial omics, video, and sensory imaging—along with the convergence of imaging and non-imaging biomedical datasets to accelerate digital health and precision medicine.