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Adaptive Non-local Means Denoising Algorithm for Cone-Beam Computed Tomography Projection Images.

, , , and . ICIG, page 33-38. IEEE Computer Society, (2009)

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Cone-Beam Computed Tomography Image Pretreatment and Segmentation., , , and . ISCID (1), page 25-28. IEEE, (2018)Cupping artifacts correction for polychromatic X-ray cone-beam computed tomography based on projection compensation and hardening behavior., , , and . Biomed. Signal Process. Control., (2020)A Self-Adapting Fast Reconstruction Method for High Resolution Images in Cone Beam CT., , , , and . ICIG, page 23-27. IEEE Computer Society, (2009)Streaking artifacts suppression for cone-beam computed tomography with the residual learning in neural network., , , , , and . Neurocomputing, (2020)Image segmentation framework based on optimal multi-method fusion., , , and . IET Image Process., 13 (1): 186-195 (2019)Complex artefact suppression for sparse reconstruction based on compensation approach in X-ray computed tomography., , , , and . IET Image Process., 17 (4): 1291-1306 (March 2023)Adaptive Non-local Means Denoising Algorithm for Cone-Beam Computed Tomography Projection Images., , , and . ICIG, page 33-38. IEEE Computer Society, (2009)Three-Dimensional Weighting in Cone Beam FBP Reconstruction and Its Transformation Over Geometries., , , , and . IEEE Trans. Biomed. Eng., 65 (6): 1235-1244 (2018)Adaptive image segmentation method based on the fuzzy c-means with spatial information., , , and . IET Image Process., 12 (5): 785-792 (2018)Adaptive windowed range-constrained Otsu method using local information., , , , and . J. Electronic Imaging, 25 (1): 013034 (2016)