Special Issue
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Topic: Artificial Intelligence and Medical Imaging in Cancer
A Special Issue of Journal of Cancer Metastasis and Treatment
ISSN 2454-2857 (Online) 2394-4722 (Print)
Submission deadline: 15 Mar 2026
Guest Editor
Assistant Guest Editors
Special Issue Introduction
Medical imaging plays a vital role in the detection, diagnosis, treatment planning, and research of cancer. Despite significant technological advances, challenges such as early detection, accurate diagnosis, and precise tumor characterization persist. These difficulties often stem from limitations in spatial resolution and sensitivity, variability in image quality, and the inherent complexity of image interpretation.
Artificial intelligence (AI) is transforming cancer imaging by enhancing image acquisition, reconstruction, analysis, and diagnostic accuracy. AI enables faster data acquisition, improved signal-to-noise ratios and image contrast, and more reliable predictions for cancer detection, diagnosis, therapy guidance, and prognosis.
However, integrating AI into medical imaging presents several key challenges. These include limited and heterogeneous datasets, inconsistent data quality standards, lack of model interpretability, concerns about bias and generalizability, and various legal and ethical considerations. Overcoming these barriers is essential to fully unlock AI’s potential in advancing cancer care.
This Special Issue invites original research articles, reviews, and clinical studies at the intersection of AI and medical imaging, with a focus on both technical innovations and clinical applications. By showcasing cutting-edge developments, this issue aims to accelerate the translation of intelligent imaging technologies into cancer research and clinical practice. We welcome contributions from researchers, clinicians, and industry experts that inspire new directions, foster collaboration, and advance the future of AI-powered cancer imaging. Join us in shaping the next generation of cancer imaging through artificial intelligence.
Potential topics:
● AI-driven cancer risk stratification;
● Early cancer detection;
● Treatment response prediction and evaluation;
● Image-guided interventions.
Keywords
Artificial Intelligence (AI), cancer imaging, deep learning, computed tomography, radiomics and radiogenomics, image reconstruction and enhancement, early cancer detection/diagnosis, medical imaging, image-guided interventions, clinical translation of AI, metastasis
Submission Deadline
Submission Information
For Author Instructions, please refer to https://www.oaepublish.com/jcmt/author_instructions
For Online Submission, please login at https://www.oaecenter.com/login?JournalId=jcmt&IssueId=jcmt25072310160
Submission Deadline: 15 Mar 2026
Contacts: Eric Zhang, Assistant Editor, ScienceEditor@oaeservice.com