Systematic Review on Learning-Based Spectral CT
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES(2024)
摘要
Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: 1) dual-energy CT (DECT) and 2) photon-counting CT (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.
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关键词
Artificial intelligence (AI),deep learning,dual-energy CT (DECT),machine learning,photon-counting CT (PCCT)
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