Deep Learning and Domain-Specific Knowledge to Segment the Liver from Synthetic Dual Energy CT Iodine Scans

We map single energy CT (SECT) scans to synthetic dual-energy CT (synth-DECT) material density iodine (MDI) scans using deep learning (DL) and demonstrate their value for liver segmentation. A 2D pix2pix (P2P) network was trained on 100 abdominal DECT scans to infer synth-DECT MDI scans from SECT sc...

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Detalles Bibliográficos
Autores principales: Mahmood, Usman, Bates, David D. B., Erdi, Yusuf E., Mannelli, Lorenzo, Corrias, Giuseppe, Kanan, Christopher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947702/
https://www.ncbi.nlm.nih.gov/pubmed/35328225
http://dx.doi.org/10.3390/diagnostics12030672

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947702/
https://www.ncbi.nlm.nih.gov/pubmed/35328225
http://dx.doi.org/10.3390/diagnostics12030672

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