Application of Artificial Intelligence in Oncologic PET Imaging
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 55
Special Issue Editors
Interests: PET/CT; nuclear medicine; neuro-oncology; lung cancer; prostate cancer; lymphoma; immunotherapy; radiomics; radioembolization
Special Issues, Collections and Topics in MDPI journals
Interests: positron emission tomography; PET/CT; PET/MRI; radiomics; machine learning; deep learning
Special Issue Information
Dear Colleagues,
Positron emission tomography (PET) has long been a cornerstone in oncologic imaging, offering detailed metabolic and functional insights into cancer biology. The integration of artificial intelligence (AI) in PET imaging presents exciting new opportunities to enhance the precision, accuracy, and clinical relevance of this powerful modality. From improving image reconstruction and quantification to developing predictive models for treatment outcomes, AI is reshaping how we approach cancer diagnosis and management through PET imaging.
This Special Issue aims to bring together cutting-edge research that explores the application of AI in oncologic PET imaging. We welcome contributions that span the full spectrum of AI-enhanced PET applications, including (but not limited to) AI-driven image analysis, segmentation, quantification and detection algorithms, and AI-assisted decision support systems and prognostication models. Of particular interest are studies focusing on novel PET radiotracers and their role in advancing oncologic care, where AI plays a critical role in optimizing imaging protocols and improving diagnostic accuracy and patient prognostication.
By publishing this Special Issue, we hope to highlight the transformative impact of AI on oncologic PET imaging and provide a comprehensive view of how these advancements are paving the way for more personalized, efficient, and effective cancer care.
We encourage authors to submit original research, review articles, and meta-analytical studies that align with these themes and push the boundaries of what is possible in AI-driven oncologic PET imaging.
Dr. Angelo Castello
Dr. Seyed Ali Mirshahvalad
Dr. Adam Farag
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- positron emission tomography (PET)
- PET/CT
- PET/MRI
- artificial intelligence
- radiomics
- machine learning
- deep learning
- convolutional neural networks
- auto-segmentation
- quantification
- theranostics
- novel radiopharmaceuticals
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
