Cargando…
Super-resolution reconstruction for parallel-beam SPECT based on deep learning and transfer learning: a preliminary simulation study
BACKGROUND: Single-photon emission computed tomography (SPECT) is widely used in the early diagnosis of major diseases such as cardiovascular disease and cancer. High-resolution (HR) imaging requires HR projection data, which typically comes with high costs. This study aimed to obtain HR SPECT image...
Autores principales: | Cheng, Zhibiao, Wen, Junhai, Zhang, Jun, Yan, Jianhua |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073770/ https://www.ncbi.nlm.nih.gov/pubmed/35530942 http://dx.doi.org/10.21037/atm-21-4363 |
Ejemplares similares
-
Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image
por: Zhang, YiNan, et al.
Publicado: (2017) -
Super-Resolution Reconstruction of Cytoskeleton Image Based on A-Net Deep Learning Network
por: Chen, Qian, et al.
Publicado: (2022) -
Super-resolution of magnetic systems using deep learning
por: Lee, D. B., et al.
Publicado: (2023) -
DLBI: deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy
por: Li, Yu, et al.
Publicado: (2018) -
SPECTnet: a deep learning neural network for SPECT image reconstruction
por: Shao, Wenyi, et al.
Publicado: (2021)