Recent Advancements in Spectral CT Imaging Techniques
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 31 January 2025 | Viewed by 787
Special Issue Editor
Interests: X-ray imaging; X-ray phase contrast imaging; dual-energy computerized tomography; photon counting CT; cone beam CT; image reconstruction; diagnostic radiography; mammography; deep learning (artificial intelligence); image denoising; iterative reconstruction; medical image processing
Special Issue Information
Dear Colleagues,
The Special Issue ‘Recent Advancements in Spectral CT Imaging Techniques’ seeks to provide an in-depth exploration of the emerging field of spectral computed tomography (CT) and its significant contributions to medical imaging. Spectral CT imaging utilizes multiple energy levels to capture detailed information about the attenuation properties of various tissue types. This novel imaging approach holds great promise in improving diagnostic accuracy, therapeutic assessment, and overall patient care.
This Special Issue invites researchers, scientists, and clinicians to present original research, comprehensive reviews, and insightful perspectives on a wide range of topics including, but not limited to, the following:
- Novel spectral CT scanner designs and technologies;
- Optimization of acquisition protocols and dose optimization techniques;
- Image reconstruction algorithms and artifact reduction strategies;
- Quantitative analysis methods for tissue characterization;
- Applications of spectral CT in specific clinical domains (e.g., oncology, cardiology, and neurology);
- Assessment of spectral CT for response evaluation in therapy and interventions;
- Exploring the potential of spectral CT in guiding personalized medicine approaches.
By collating and disseminating research on the aforementioned topics, this Special Issue aims to foster collaboration among researchers and facilitate the integration of spectral CT into routine clinical practice, ultimately enhancing our understanding of disease processes, improving diagnostic accuracy, and promoting better patient outcomes.
Prof. Dr. Yongshuai Ge
Guest Editor
Manuscript Submission Information
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Keywords
- spectral CT
- computed tomography
- medical imaging
- image reconstruction
- diagnostic radiography
- deep learning (artificial intelligence)
- clinical applications
- X-ray imaging
- biological tissues
- cancer
- therapeutic assessment
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