An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.

Papetti DM, Van Abeelen K, Davies R, Menè R, Heilbron F, Perelli FP, Artico J, Seraphim A, Moon JC, Parati G, Xue H, Kellman P, Badano LP, Besozzi D, Nobile MS, Torlasco C

Open source

DOI
10.1016/j.cmpb.2022.107321
Published
2023 Feb
Container
Computer methods and programs in biomedicine
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1016/j.cmpb.2022.107321,
  title = {An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.},
  author = {Papetti DM and Van Abeelen K and Davies R and Menè R and Heilbron F and Perelli FP and Artico J and Seraphim A and Moon JC and Parati G and Xue H and Kellman P and Badano LP and Besozzi D and Nobile MS and Torlasco C},
  year = {2023},
  journal = {Computer methods and programs in biomedicine},
  doi = {10.1016/j.cmpb.2022.107321},
  url = {https://doi.org/10.1016/j.cmpb.2022.107321}
}

RIS

TY  - JOUR
TI  - An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.
AU  - Papetti DM
AU  - Van Abeelen K
AU  - Davies R
AU  - Menè R
AU  - Heilbron F
AU  - Perelli FP
AU  - Artico J
AU  - Seraphim A
AU  - Moon JC
AU  - Parati G
AU  - Xue H
AU  - Kellman P
AU  - Badano LP
AU  - Besozzi D
AU  - Nobile MS
AU  - Torlasco C
PY  - 2023
JO  - Computer methods and programs in biomedicine
DO  - 10.1016/j.cmpb.2022.107321
UR  - https://doi.org/10.1016/j.cmpb.2022.107321
ER  - 

APA

DM, P., K, V. A., R, D., R, M., F, H., FP, P., J, A., A, S., JC, M., G, P., H, X., P, K., LP, B., D, B., MS, N., & C, T. (2023). An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.. Computer methods and programs in biomedicine. https://doi.org/10.1016/j.cmpb.2022.107321

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