2016
DOI: 10.1109/jphot.2016.2606239
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An Optimized Attenuation Compensation and Contrast Enhancement Algorithm Without Pseudocharacteristics in Intravascular OCT Imaging

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Cited by 5 publications
(2 citation statements)
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“…Then, he compared IVOCT images with different enhancement coefficient values to evaluate the effect of each algorithm based on the improvement of depth visibility, contrast enhancement, and feature retention. Although his research can derive the best attenuation coefficient for attenuation compensation and contrast enhancement algorithms, the research lacks systematic contrast [ 1 ]. KouvAa aims to compare the diagnostic accuracy of axial chest CT, other imaging techniques, and image reconstruction algorithms with fiberoptic bronchoscopy (FOB) endoscopy in patients with newly discovered endobronchial lesions.…”
Section: Introductionmentioning
confidence: 99%
“…Then, he compared IVOCT images with different enhancement coefficient values to evaluate the effect of each algorithm based on the improvement of depth visibility, contrast enhancement, and feature retention. Although his research can derive the best attenuation coefficient for attenuation compensation and contrast enhancement algorithms, the research lacks systematic contrast [ 1 ]. KouvAa aims to compare the diagnostic accuracy of axial chest CT, other imaging techniques, and image reconstruction algorithms with fiberoptic bronchoscopy (FOB) endoscopy in patients with newly discovered endobronchial lesions.…”
Section: Introductionmentioning
confidence: 99%
“…Some researchers held that the spatial information of the image is more suitable for image enhancement than the firstorder statistics. For example, Zhou et al [6] put forward the context and variation contrast enhancement algorithm, which adjusts the image with two-dimensional (2D) histogram. Under the best contrast tone mapping framework, Song et al [7] proposed a new image enhancement algorithm that overcomes the limitations of contrast enhancement histogram, using the joint probability of spatial information.…”
Section: Image Enhancementmentioning
confidence: 99%