The Advanced Role of Artificial Intelligence in Computed Tomography (CT)
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Machine Learning and Artificial Intelligence in Diagnostics".
Deadline for manuscript submissions: 30 April 2025 | Viewed by 5731
Special Issue Editor
Interests: CT; machine learning; deep learning; tumor classification; medical images segmentation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computed tomography (CT) has revolutionized the field of medical imaging by providing detailed and accurate images of the human body. The latest advancements in artificial intelligence (AI) have provided new opportunities to further enhance the power and efficiency of CT. With this Special Issue, we invite researchers and experts in the field of medical imaging to explore the advanced role of AI in CT. The integration of AI into CT imaging has led to significant improvements in image quality, interpretation, and protocol optimization. AI-based image reconstruction and denoising techniques have the potential to reduce noise and artifacts, thereby enhancing the clarity and diagnostic accuracy of CT images. AI-based image segmentation and analysis have been used to aid in the identification and characterization of pathological tissue, improving the precision and speed of disease detection. Moreover, AI-assisted diagnosis and interpretation of CT images have the potential to improve the reliability and consistency of clinical decisions, leading to more accurate and timely patient care.
In addition, AI-based radiation dose optimization has the potential to reduce patient exposure to ionizing radiation while maintaining image quality. AI-based motion correction and artifact reduction techniques have the potential to mitigate the effects of patient motion and reduce image distortion. AI-based prediction of treatment response and prognosis using CT has the potential to guide personalized treatment decisions and improve patient outcomes. Furthermore, AI-based CT image registration and fusion techniques have the potential to integrate CT images with other imaging modalities, providing a more comprehensive view of a patient’s anatomy and pathology. The integration of AI into CT imaging raises important ethical and legal questions, such as responsibility for the accuracy and safety of the AI algorithms used and the potential impact on patient privacy. As such, the ethical and legal implications of AI-based CT imaging will also considered in this Special Issue.
In summary, this Special Issue seeks to bring together original research articles, review papers, and case studies that demonstrate the latest advancements in AI for CT, their potential benefits and challenges, and their impact on clinical practice. We invite contributions from researchers and experts in medical imaging, AI, computer science, and related fields. The submitted manuscripts will undergo rigorous peer review, with acceptance based on originality, significance, and relevance to the theme of the Special Issue.
Dr. Steven Fernandes
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
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