Artificial Intelligence in Image-Based Diagnostics of Oncological and Neurological Disorders

Dear Colleagues,

Diagnostic imaging has experienced major changes in recent years. Radiological and nuclear medicine modalities represent the option of choice to investigate the main oncological and neurological diseases. The improving capabilities of the imaging devices and the increasing availability of storing, sharing and computing facilities have been generating larger and larger amounts of data. Consequently, there has been increasing attention on the development of computational methods for the extraction of objective imaging features (biomarkers) capable of correlating with disease phenotype, clinical outcome and/or response to treatment. The combined use of imaging data, biomarkers and artificial intelligence techniques makes it possible to build powerful predictive models which can assist the physician in the management of patients with a wide range of disorders, particularly oncological and neurological, ultimately leading to personalised treatment and better clinical outcome. However, there are still open challenges before these methods can be translated into clinical practice. Critical to this process, for instance, are standardisation, strong interdisciplinary cooperation, and the availability of centralised repositories of annotated data.  

This Special Issue wants to provide a forum to discuss challenges, discoveries and opportunities in the field, with specific focus on the diagnosis of oncological and neurological disorders by radiological and nuclear medicine modalities. We encourage the submission research papers as well as review articles; comparative evaluations and new datasets are also welcome.

Dr. Barbara Palumbo
Prof. Dr. Angela Spanu
Prof. Dr. Luca Brunese
Dr. Francesco Bianconi
Guest Editors

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