Special Issue "PET/CT Imaging in Oncology: Clinical Updates and Perspectives"
A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Nuclear Medicine & Radiology".
Deadline for manuscript submissions: 30 April 2023 | Viewed by 14232
Special Issue Editors
Interests: nuclear medicine; radioactive iodine therapy; thyroid disease; differentiated thyroid cancer; PET/CT; pediatrics; brain tumors; neuroblastoma; 131I MIBG therapy; prostate cancer; ovarian cancer; hyperparathyroidism
Special Issues, Collections and Topics in MDPI journals
Interests: nuclear medicine; radioisotope therapy; PET/CT; hematology; plaque imaging; image segmentation; texture analysis; radiomics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
PET/CT has been the fastest-growing image modality in recent decades. This growth has been bolstered, on one hand, by the approval of new radiotracers, which were instrumental in addressing the known limitations of FDG. On the other hand, the constant research of new possible indications of FDG-PET has led to the implementation of this tracer in many new clinical settings (e.g., image-guided surgery). Finally, advanced image analysis (including, but not limited to radiomics, machine learning, automatic target segmentation, computer vision, augmented reality etc.) has given new value to the acquired data and has the potential to increase the amount of information that the imaging specialist and the clinicians can extract from the images. These aspects represent the pillars that will support the further growth of nuclear medicine. This Special Issue aims to include a selection of high-quality papers on the clinical and research applications of FDG and non-FDG tracers. Moreover, it will include scientific reports of advanced methods of image analysis, with a particular focus on image-based dosimetry and quantification, automatic segmentation, tumor burden calculation, computer-assisted diagnosis, and machine learning methods. The overall goal of this issue is to provide an overview on the future directions of molecular imaging research, and, more in general, of innovative image analysis techniques.
Dr. Arnoldo Piccardo
Dr. Francesco Fiz
Guest Editors
Manuscript Submission Information
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Keywords
- Non FDG radiopharmaceuticals
- Segmentation
- Tumor burden calculation
- Machine learning
- Neural networks
- Deep learning
- Artificial Intelligence