Advances in Medical Physics and Quantitative Imaging

Dear Colleagues,

Medical physics and quantitative imaging have rapidly evolved in recent years, driven by advances in imaging technologies, computational modeling, and data analysis methods. These advances allow for the increasingly precise, quantitative assessment of anatomy, function, and molecular processes, enabling improved diagnostics, treatment planning, and therapy monitoring. However, challenges remain in translating innovations from research settings into robust clinical applications and in fully exploiting quantitative imaging for personalized medicine.

This Special Issue aims to provide a platform for the latest research on cutting-edge developments in medical physics and quantitative imaging, emphasizing both methodological advances and their applications in clinical or preclinical settings. We invite contributions that address fundamental principles, innovative imaging techniques, quantitative data analysis methods, and integration with other diagnostic or therapeutic modalities.

Potential topics include, but are not limited to, the following:

• Novel imaging modalities and hybrid imaging systems (PET/MR, SPECT/CT, multi-spectral CT, functional MRI, etc.);
• Advances in image reconstruction, modeling, and quantitative analysis;
• Radiation dose optimization and dosimetry in clinical imaging and therapy;
• Machine learning and AI-driven quantitative imaging;
• Multi-parametric and multi-modal imaging for disease characterization;
• Development and validation of imaging biomarkers;
• Real-time imaging techniques and in-procedure guidance systems;
• Standardization, reproducibility, and quality assurance in quantitative imaging;
• Translational studies bridging preclinical imaging and clinical applications;
• Novel computational methods for image processing, the correction of artifacts, or uncertainty quantification.

Original research articles highlighting innovative methods, comparative studies, and translational applications are particularly encouraged. Review articles that provide a comprehensive overviews of emerging technologies or methodological approaches are also welcome.

We aim to gather a collection of high-quality contributions that advance the understanding, application, and clinical translation of medical physics and quantitative imaging technologies.

Dr. Oleksandra V. Ivashchenko
Guest Editor

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. Applied Sciences 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 2400 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.

• medical physics
• quantitative imaging
• hybrid imaging
• image reconstruction
• dosimetry and radiation dose optimization
• imaging biomarkers
• functional and molecular imaging
• machine learning in medical imaging
• multi-parametric imaging
• translational imaging studies