Advances in Cancer Imaging: Evolving Role of Radiomics and Artificial Intelligence
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".
Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 323
Special Issue Editor
Interests: cancer imaging; artificial intelligence; radiomics; brain metastasis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Non-invasive tumor diagnosis and classification has long been a crucial issue in clinical decision making. Among many methods available, imaging examinations via ultrasound, CT, MRI, PET, or SPECT are commonly adopted which provide anatomical/functional information on the tumor.
Recently, radiomics and artificial intelligence (AI) provide new possibilities for imaging data interpretation and form an automatic pipeline for disease classification or segmentation. Radiomics, empowered by machine learning algorithms, can classify the tumor lesions only based on anatomical scans. Auto-segmentation by AI may facilitate early diagnoses and generate masks for radiomic analyses. Radiomics or AI studies based on multimodality imaging data (MRI plus PET, MRI plus CT, and so on) yield a better predictive performance.
Hopefully, technically novel, clinically relevant, and meticulously designed studies on cancer imaging contribute to improved patient care.
Dr. Shuncong Wang
Guest Editor
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.
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Keywords
- multi-modality imaging
- artificial intelligence
- radiomics
- MRI
- CT
- ultrasound
- intervention
- diagnosis
- classification
- differentiation
