Magnetic resonance image enhancement and segmentation using conventional and deep learning denoising techniques for dynamic cerebral angiography.
- DOI
- 10.1007/s13755-025-00406-x
- Published
- 2026 Dec
- Container
- Health information science and systems
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1007/s13755-025-00406-x,
title = {Magnetic resonance image enhancement and segmentation using conventional and deep learning denoising techniques for dynamic cerebral angiography.},
author = {Herrera D and Ochoa-Ruiz G and Stephan-Otto C and Gonzalez-Mendoza M and Munuera J and Mata C},
year = {2026},
journal = {Health information science and systems},
doi = {10.1007/s13755-025-00406-x},
url = {https://doi.org/10.1007/s13755-025-00406-x}
}RIS
TY - JOUR TI - Magnetic resonance image enhancement and segmentation using conventional and deep learning denoising techniques for dynamic cerebral angiography. AU - Herrera D AU - Ochoa-Ruiz G AU - Stephan-Otto C AU - Gonzalez-Mendoza M AU - Munuera J AU - Mata C PY - 2026 JO - Health information science and systems DO - 10.1007/s13755-025-00406-x UR - https://doi.org/10.1007/s13755-025-00406-x ER -
APA
D, H., G, O., C, S., M, G., J, M., & C, M. (2026). Magnetic resonance image enhancement and segmentation using conventional and deep learning denoising techniques for dynamic cerebral angiography.. Health information science and systems. https://doi.org/10.1007/s13755-025-00406-x
Source records
- pubmed · retrieved 2026-09-26T03:02:05.133Z
- europe-pmc · retrieved 2026-09-26T03:02:05.127Z