The integration of Artificial Intelligence into medical image diagnosis represents a transformative leap in the field of healthcare, particularly in oncology and neuroscience. This special issue aims to explore the significant advancements AI has made in enhancing the accuracy, speed, and efficiency of diagnostic processes. By leveraging cutting-edge machine learning and deep learning algorithms, AI has demonstrated immense potential in detecting and characterizing tumors, as well as in providing insights into complex neurological conditions. In oncology, AI systems are increasingly used to analyze medical images for early detection of cancer, tumor segmentation, and treatment planning, while in neuroscience, AI is advancing the understanding of brain disorders through image-based analysis of structural and functional brain data. This issue highlights the ongoing innovations and challenges in applying AI to medical imaging, emphasizing its role in improving clinical outcomes, supporting personalized treatments, and ultimately revolutionizing patient care.

In recent years, the application of AI in medical imaging has rapidly evolved. For instance, AI algorithms have revolutionized radiology, particularly in areas like detecting and classifying lung nodules, tumors in different medical image modalities (e.g., MRI, CT, and PET scans), exploring explainable approaches to digging underlying mechanism on neurosciences, smart guidance for clinical practice based on AI-driven smart guidance for clinical practice based on medical image techniques. Generally, AI is paving the way for personalized healthcare by aiding in precise diagnosis, treatment planning, and prognosis prediction.

This special issue, "Advancing the Integration of Artificial Intelligence in Medical Imaging for Organ Medicine," aims to bring together cutting-edge research that pushes the limits of AI in tackling the complex challenges within medical imaging. We invite contributions that explore innovative AI model training techniques in medical imaging, as well as groundbreaking AI approaches that improve the accuracy, speed, and efficiency of diagnostic imaging. Topics of interest encompass, but are not limited to, the development of advanced AI models, the application of AI methods for medical data processing, the role of AI in surgical practices using medical images, and translational AI studies bridging preclinical research with clinical applications.

Through a comprehensive compilation of original research, reviews, and expert perspectives, this special issue intends to provide an interdisciplinary platform that showcases the full scope of AI applications in medical imaging. Our goal is to deepen understanding of the current challenges and opportunities in this fast-evolving field, encourage cross-disciplinary collaboration, and ultimately drive the development of transformative therapies that address critical gaps in organ medicine.

Topics for this call for papers include but are not restricted to:

• The usage of AI on oncology diagnoses
• The usage of AI on neuroscience exploration
• The usage of AI on surgical or clinical treatment guidance
• The innovative AI model training techniques in medical imaging
• The AI methods for medical data processing

Guest Editors:

Dr. Jianhua Wang
The first affiliated hospital of Xiamen University
China

Dr. Wei Qian
Northeastern University
China

Submission Guidelines/Instructions

Please refer to the Author Guidelines to prepare your manuscript. When submitting your manuscript, please answer the question: "Is this submission for a special issue?" by selecting the special issue title from the drop-down list.