About this Research Topic
This Research Topic aims to explore AI/machine learning applications for the improvement of medical workflow, procedure, diagnostic workup, etc., that relate to radiological images. The potential applications may include new imaging methods for better efficiency or image quality, workflow optimization for quality control and image reading, workup improvement for image diagnosis, cancer risk prediction, supportive visualization and analytic tools for treatment procedures, like planning, follow-up, and so on. The content of an AI/machine learning application can be technological development, clinical evaluation, or the exploitation of new directions that could change the current paradigm of medical image-related processes. In particular, AI applications equipped with the cutting-edge generative pre-trained transformer (GPT) as well as the exploratory image-related scenes incorporated with the question and answer (Q&A) scheme, empowered by ChatGPT and other advanced language models, are also highly welcome.
We call for Original Research, Methods, Systematic Review, Perspective, Clinical Trials, Case Reports, and Brief Research Reports about AI/machine applications for medical image-related workflows. The potential themes are shown below, but not limited to:
- Computer-aided detection of abnormalities in medical images
- Computer-aided diagnosis
- Risk prediction for cancers
- Computer-aided surgical or treatment planning
- Medical workflow optimization
- Computer-aided image quality control
- New medical imaging methods with AI techniques
- Triaging for critical findings
- Prognosis prediction with image cues
- Clinical evaluation for AI applications
Topic Editor Jie-Zhi Cheng is is employed by Shanghai United Imaging Intelligence Co., Ltd. Other Topic Editors declare no conflicts of interest with the Research Topic.
Keywords: Computer-aided medical image quality control, Computer-aided diagnosis and treatment, Computer-aided risk analysis and prediction, Computer-aided treatment planning, Computer-aided prognosis prediction
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.