Artificial Intelligence in Image-Based Diagnostics of Oncological and Neurological Disorders 2.0
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 2199
Special Issue Editors
Interests: nuclear medicine; image-based diagnostics; artificial intelligence; PET/CT; SPECT; SPECT/CT; radiomics; oncology; neurodegenerative disorders
Special Issues, Collections and Topics in MDPI journals
Interests: nuclear medicine; image-based diagnostics; SPECT; SPECT/CT; PET/CT; molecular breast imaging; oncology (breast cancer, lung cancer, thyroid cancer, neuroendocrine tumors, and prostate cancer); radiomics; neurodegenerative disorders; radiometabolic therapy
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; image-based diagnostics; CT; MRI; radiology; radiomics; oncology
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; computational imaging; computer vision; image processing; medical image analysis; radiomics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Diagnostic imaging has undergone major changes in recent years. Radiological and nuclear medicine imaging play a pivotal role in the diagnosis, stratification and follow-up of oncological and neurological disorders. 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 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 personalized 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 standardization, man–machine interaction, strong interdisciplinary cooperation and the availability of centralized repositories of annotated data.
This Special Issue aims to provide a forum to discuss challenges, discoveries and opportunities in the field, with specific focus on the diagnosis of oncological and neurological disorders via radiological and nuclear medicine modalities. We encourage the submission of 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
Manuscript Submission Information
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Keywords
- artificial intelligence in diagnostic imaging
- computer-assisted diagnosis and prognostication
- data mining and big data
- deep learning
- image processing (including acquisition, pre-processing, segmentation and feature extraction)
- radiology
- radiomics
- nuclear medicine
- imaging modalities (including CT, MRI, PET, PET/CT, PET/MRI, SPECT, SPECT/CT)
- oncological and neurological disorders
- personalized medicine
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