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Motivation and objectives
Medical images make up a large percentage of healthcare data. Medical experts draw insights from that data to make better decisions about diagnostics and treatments. The evaluation of the medical image quality and its applications is crucial for medical technologies, products, and services. Actual research encompasses a wide range of methodologies on medical quality assessment: subjective tests may be based on the mean opinion score (MOS) or a specific medical task; objective metrics may be the prediction of the MOS or the modeling of the task procedure. But the topic and its applications still remain a great challenge considering the large diversity of medical imaging modalities and pathologies.
The goal of this special session is to bring together researchers to exchange the latest advances in medical image quality assessment, as well as its applications in medical image processing, computer-aided diagnosis, image- or video- guided procedures, medical image perception and interpretation, digital and computational pathology, biomedical engineering, display and ergonomic design, etc.
Topics of interest
We are seeking papers that include, but are not limited to, the following topics:
Experimental protocols with human observers for medical image quality assessment.
Publicly accessible new datasets in this domain.
Objective metrics for medical image quality assessment.
Task-based quality assessment (e.g. model observers).
Quality-guided medical image processing (enhancement, segmentation, coding, and watermarking, etc.).
Human visual attention modeling for medical images, helpful for quality assessment.
Preliminary works providing interesting insights in this domain (for short papers, for example).
Organizers
Lu Zhang (Lu.Ge@insa-rennes.fr), INSA Rennes/Institut d'Electronique et des Technologies du numéRique (IETR), France
Meriem Outtas (Meriem.Outtas@insa-rennes.fr), INSA Rennes/Institut d'Electronique et des Technologies du numéRique (IETR), France
Lucie Lévêque (Lucie.Leveque@univ-nantes.fr), Laboratoire des Sciences du Numérique de Nantes (LS2N), Nantes Université, France
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