Anatomical evaluation of deep-learning synthetic computed tomography images generated from male pelvis cone-beam computed tomography
Background and purpose: To improve cone-beam computed tomography (CBCT), deep-learning (DL)-models are being explored to generate synthetic CTs (sCT). The sCT evaluation is mainly focused on image quality and CT number accuracy. However, correct representation of daily anatomy of the CBCT is also im...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2023-01-01
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Series: | Physics and Imaging in Radiation Oncology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405631623000076 |