Generation of virtual monoenergetic images at 40 keV of the upper abdomen and image quality evaluation based on generative adversarial networks
Hua Zhong,
Qianwen Huang,
Xiaoli Zheng
et al.
Abstract:Background
Abdominal CT scans are vital for diagnosing abdominal diseases but have limitations in tissue analysis and soft tissue detection. Dual-energy CT (DECT) can improve these issues by offering low keV virtual monoenergetic images (VMI), enhancing lesion detection and tissue characterization. However, its cost limits widespread use.
Purpose
To develop a model that converts conventional images (CI) into generative virtual monoenergetic images … Show more
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