Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study

Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study

Abstract Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle study, a deep learning approach to multi-mate...

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Main Authors: Jayasai R. Rajagopal, Saikiran Rapaka, Faraz Farhadi, Ehsan Abadi, W. Paul Segars, Tristan Nowak, Puneet Sharma, William F. Pritchard, Ashkan Malayeri, Elizabeth C. Jones, Ehsan Samei, Pooyan Sahbaee
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Material decomposition
Spectral CT
Computed tomography
Simulation
Deep learning
Online Access:https://doi.org/10.1038/s41598-025-09739-9
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https://doi.org/10.1038/s41598-025-09739-9

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