An Update on Radiological Diagnosis in 2024
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Medical Imaging and Theranostics".
Deadline for manuscript submissions: 31 December 2024 | Viewed by 40
Special Issue Editors
Interests: neuroradiology; MRI; focused ultrasound; tremor; spine imaging
Special Issues, Collections and Topics in MDPI journals
Interests: MRI; MSK imaging; bone tumors; soft tiffue tumors; DTI; radiomics; cardiac CT; cardiac MRI; prostate MRI; MSK ultrasound
Special Issues, Collections and Topics in MDPI journals
Interests: CT; vasculare imaging; oncologic imaging; interventional radiology; radiomics
Special Issue Information
Dear Colleagues,
The radiological diagnosis landscape has undergone profound transformations, evolving significantly through technological advancements and the integration of artificial intelligence. These enhancements not only redefine diagnostic accuracy but also augment the radiologist's role in clinical decision-making as of 2024. This SI aims to provide a comprehensive update on the current state of radiological techniques, focusing on recent innovations in imaging technologies, the application of machine learning algorithms, and their implications for patient care. By examining cutting-edge developments in hardware and software and their synergistic interactions, we will explore how these advancements contribute to improved diagnostic precision and patient outcomes. Furthermore, this review discusses the ethical considerations and challenges that accompany the implementation of AI in radiology, highlighting the need for balanced integration of technology in healthcare practices. Through this analysis, we aim to elucidate the pivotal changes in radiological practices, emphasizing their impact on both medical professionals and the healthcare system at large.
Dr. Federico Bruno
Dr. Raffaele Natella
Dr. Nicola Maria Lucarelli
Guest Editors
Manuscript Submission Information
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Keywords
- radiological diagnosis
- radiological techniques
- precision medicine
- imaging
- quantitative imaging
- artificial intelligence
- machine learning
