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Special issue on Machine learning in radiation based medical sciences

16 Novembre 2017

Catégorie : Revues

IEEE Transactions on Radiation & Plasma Medical Sciences


The IEEE TRPMS encompasses radiation- and plasma-related technologies for medical applications, including radiation detectors, imaging instrumentation, radiation-based image reconstruction, data analysis and image processing, and clinical/preclinical evaluation of imaging systems. We would like to organize a special issue on the machine learning applications in radiation medical sciences, in collaboration with the Editorial Board of the IEEE TRPMS, to be published in 2018.

Machine learning is a very active field of research that has found numerous applications in various fields of the medical sciences, from image reconstruction or dosimetry, to image analysis and processing. In the last few years, the field of machine learning has also seen the fast development and impressive results of deep learning based techniques. We would like to invite authors to submit papers related to the use of established or newly developed machine learning techniques to applications related to radiation medical sciences. The topics include but are not limited to:

  • X-ray CT, Dual-/multi-energy CT, PET, PET/CT and PET/MR static and dynamic imaging
  • Image reconstruction and estimation
  • Multimodality fusion and association
  • Dosimetry, planification
  • Image processing (denoising/filtering, partial volume effects correction, artifacts correction…)
  • Image segmentation and classification
  • Image analysis and characterization, radiomics, radiogenomics

Authors must submit papers digitally according to, indicating that the submission is aimed for this special issue in the cover letter. Authors are encouraged to contact the guest editors to determine suitability of their submission for this special issue.

Guest Editors

Mathieu Hatt, PhD


IBSAM, University of Brest


Jinyi Qi, PhD

UC Davis

Biomedical Engineering school

Chintan Parmar, PhD

Department of Radiation Oncology

Dana-Farber Cancer Institute

Harvard Medical School


Issam El Naqa, PhD

Department of Radiation Oncology

Physics division, University of Michigan



+33 2 98 01 81 11

(530) 754-6142





  • Submission of manuscripts: March 1, 2018
  • Acceptance/rejection notification: May 15, 2018
  • Revised manuscripts due: July 30, 2018
  • Publication: November 1, 2018 (Tentatively)