A Fully Automated Segment-Specific CCTA Plaque Quantification Workflow using Deep Learning.

Wang H, Hou X, Liu Z, Yang J, Shen J, Tang Z, Zhang J, Chen T, Yang J, Guo J

DOI: 10.1007/s10278-026-02478-x
Published: 2026 Nov 5
Container: Journal of imaging informatics in medicine
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s10278-026-02478-x,
  title = {A Fully Automated Segment-Specific CCTA Plaque Quantification Workflow using Deep Learning.},
  author = {Wang H and Hou X and Liu Z and Yang J and Shen J and Tang Z and Zhang J and Chen T and Yang J and Guo J},
  year = {2026},
  journal = {Journal of imaging informatics in medicine},
  doi = {10.1007/s10278-026-02478-x},
  url = {https://doi.org/10.1007/s10278-026-02478-x}
}

RIS

TY  - JOUR
TI  - A Fully Automated Segment-Specific CCTA Plaque Quantification Workflow using Deep Learning.
AU  - Wang H
AU  - Hou X
AU  - Liu Z
AU  - Yang J
AU  - Shen J
AU  - Tang Z
AU  - Zhang J
AU  - Chen T
AU  - Yang J
AU  - Guo J
PY  - 2026
JO  - Journal of imaging informatics in medicine
DO  - 10.1007/s10278-026-02478-x
UR  - https://doi.org/10.1007/s10278-026-02478-x
ER  -

APA

H, W., X, H., Z, L., J, Y., J, S., Z, T., J, Z., T, C., J, Y., & J, G. (2026). A Fully Automated Segment-Specific CCTA Plaque Quantification Workflow using Deep Learning.. Journal of imaging informatics in medicine. https://doi.org/10.1007/s10278-026-02478-x

Source records

pubmed · retrieved 2026-11-10T11:34:26.338Z