Advances in Cancer Imaging, Radiomics, and Radiotherapy
A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Oncology".
Deadline for manuscript submissions: 30 August 2026 | Viewed by 62
Special Issue Editor
Interests: machine learning; classification; neural networks and artificial intelligence; meta-analysis; cancer; biostatistics; epidemiology; bioinformatics
Special Issue Information
Dear Colleagues,
Cancer is an important health issue in the world. Imaging is important in cancer treatment. Cancer imaging involves X-ray, computed tomography (CT), magnetic resonance imaging (MRI), bone scan, Positron Emission Tomography (PET), endoscopy, ultrasound, pathology imaging, mammography, and so on. Imaging can be used in the pre-treatment of cancer, mid-treatment of cancer, and post-treatment of cancer. For the pre-treatment of cancer, imaging can be used for detection and staging. For mid-treatment of cancer, imaging can be used for adaptive treatment. For post-treatment of cancer, imaging can be used for follow-up or response assessment. The main treatments of cancer involve surgery, radiotherapy, and systemic therapy. Radiomics is a popular research method for classification and prognosis prediction in the field of cancer. Radiomics can be applied to almost all kinds of cancer imaging. The traditional methods of extracting radiomics features from imaging require the creation of regions of interest (ROIs). Clinical radiotherapy workflows involve contouring of imaging, which can serve as an ROI of radiomics. As a result, it is reasonable to combine radiomics and radiotherapy. This Special Issue on “Advances in Cancer Imaging, Radiomics, and Radiotherapy” aims to publish papers about Advances in Cancer Imaging, Radiomics, and Radiotherapy.
Dr. Yung-Shuo Kao
Guest Editor
Manuscript Submission Information
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Keywords
- radiomics
- radiotherapy
- cancer imaging
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