Artificial Intelligence in Oncologic Imaging: Advances in Medical Image Segmentation and Predictive Modelling
A special issue of Medical Sciences (ISSN 2076-3271).
Deadline for manuscript submissions: 30 September 2026 | Viewed by 77
Special Issue Editors
Interests: artificial intelligence; biomedical image processing; decision-making systems; DICOM standard; graphical user interface
Special Issue Information
Dear Colleagues,
In recent years, artificial intelligence (AI) has transformed oncology by introducing powerful new methods for diagnosing, segmenting, and monitoring medical images across a wide spectrum of clinical applications. This Special Issue seeks original contributions that advance the integration of AI into oncologic imaging and related domains. Key areas of interest include radiomic analysis through multimodal deep neural networks, medical image segmentation for lesion detection, boundary delineation, treatment planning, as well as predictive modelling using machine learning, deep learning, and generative frameworks such as Vision–Language Models. These innovations enhance our capacity to interpret complex biomedical data, offering new insights into disease characterisation and supporting personalised therapeutic strategies. By highlighting current challenges and opportunities, this Special Issue aims to foster deeper integration of AI technologies within precision medicine.
Dr. Orazio Gambino
Dr. Salvatore Contino
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- medical image segmentation
- oncologic imaging
- radiomics
- deep learning
- machine learning
- predictive modelling
- vision language models
- multimodal imaging
- precision medicine
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