Innovations in Imaging for Radiation Oncology

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 34

Special Issue Editors


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Guest Editor
Department of Radiology, Division of Musculoskeletal Imaging and Intervention, University of Washington, Seattle, WA 98105, USA
Interests: radiation oncology; diagnostic imaging; artificial intelligence; radiomics; tumor detection; molecular imaging; treatment planning; radiogenomics

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Guest Editor Assistant
Department of Radiology, Division of Musculoskeletal Imaging and Intervention, University of Washington, Seattle, WA 98105, USA
Interests: radiation oncology; diagnostic imaging; artificial intelligence; radiomics; tumor detection; molecular imaging; treatment planning; radiogenomics

Special Issue Information

Dear Colleagues,

Radiation oncology, a cornerstone of cancer management, relies heavily on the advancements in radiology for precise treatment planning and monitoring. Imaging modalities like CT, MRI, and PET-CT play a pivotal role in defining tumor boundaries, assessing treatment response, and adapting therapy in real-time.
The field of radiation oncology has witnessed significant advancements in diagnostic techniques, transforming patient care through enhanced precision and accuracy. This Special Issue aims to explore the latest developments in diagnostic imaging, artificial intelligence applications, and molecular imaging techniques that are shaping the future of radiation oncology. Contributions will focus on innovations that improve tumor detection and treatment responses, optimize radiation outcomes, and prevent different complications of radiation. Topics may include, but are not limited to, advanced imaging modalities, AI-based decision support systems, radiomics and radiogenomics, and real-time adaptive imaging techniques. By highlighting these cutting-edge advancements, the issue seeks to bridge the gap between diagnostic imaging and therapeutic applications, fostering interdisciplinary collaboration to enhance cancer treatment outcomes. This issue invites original research, reviews, and case studies from researchers and clinicians who are pioneering these transformative diagnostic approaches.

Dr. Sara Haseli
Dr. Arash Azhideh
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. Diagnostics is an international peer-reviewed open access semimonthly 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 2600 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

  • radiation oncology
  • diagnostic imaging
  • artificial intelligence
  • radiomics
  • tumor detection
  • molecular imaging
  • treatment planning
  • radiogenomics

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Published Papers

This special issue is now open for submission.
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