Ander Biguri
Papers
1
Total Citations
46
H-Index
1
About
Ander Biguri is a leading researcher in biomedical imaging, with a primary focus on cone-beam computed tomography (CBCT) and advanced tomographic reconstruction. His most-cited work, a comprehensive 2022 review on source-detector trajectory optimization in CBCT, has already garnered 46 citations, establishing him as a key voice in the field. Biguri’s major contributions center on developing novel algorithms for non-circular scanning trajectories, which significantly enhance image quality in critical applications like image-guided surgery, radiation therapy, and diagnostic imaging for breast and orthopaedic conditions. By systematically analyzing and advancing state-of-the-art trajectory optimization methods, he has helped bridge the gap between theoretical imaging physics and practical clinical deployment. His research addresses fundamental challenges in CBCT—such as reducing artifacts and improving dose efficiency—making high-quality imaging more accessible and reliable. Biguri’s work is particularly notable for its interdisciplinary impact, influencing both engineering design and clinical protocols. For students and researchers, his contributions offer a clear pathway into the future of adaptive, patient-specific CT imaging, where trajectory planning is as important as reconstruction itself.
Research Focus
Key Achievements
Top Papers
- 1