X-Ray Scatter Correction by Deep Semi-supervised Learning of Simulated Projections with Beam-hole Array

In nondestructive testing and evaluation using cone-beam X-ray computed tomography (CBCT), X-ray scattering is a major cause of degrading the quality of CT images. To correct the negative effects of scattering, recent studies focused on the deep convolutional neural network (DCNN) for fast and accur...

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Veröffentlicht in:	E-journal of Nondestructive Testing 2023-03, Vol.28 (3)
Hauptverfasser:	Hattori, Haruki, Yatagawa, Tatsuya, Ohtake, Yutaka, Suzuki, Hiromasa
Format:	Artikel
Sprache:	eng
Online-Zugang:	Volltext
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