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CSTGV55GT0
The term ‘texture’ refers to patterns arranged in an order in a line or a curve. Textures allow one to make a meaningful interpretation of certain geometric regularity of spatially repeated patterns. In addition, texture also exhibits useful information about spatial distribution of color or gray intensities in an image. Correct interpretation of latent textures of various tissues in a body is an important requirement for a surgeon as a preoperative measure. In this context, extraction of textures in an MR scanned 3D image would assist a medical professional in the preoperative decision making process. This paper proposes a novel technique for extracting directional textures of a 3D MR image in all three axes separately.
Arun Kumar A. 2021. \u201cTexture Classification of 3D MR Color Images using 3D Orthogonal Rank Filters\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 21 (GJCST Volume 21 Issue F1): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 101
Country: India
Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision
Authors: Arun Kumar A (PhD/Dr. count: 0)
View Count (all-time): 238
Total Views (Real + Logic): 4003
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Publish Date: 2021 03, Wed
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The term ‘texture’ refers to patterns arranged in an order in a line or a curve. Textures allow one to make a meaningful interpretation of certain geometric regularity of spatially repeated patterns. In addition, texture also exhibits useful information about spatial distribution of color or gray intensities in an image. Correct interpretation of latent textures of various tissues in a body is an important requirement for a surgeon as a preoperative measure. In this context, extraction of textures in an MR scanned 3D image would assist a medical professional in the preoperative decision making process. This paper proposes a novel technique for extracting directional textures of a 3D MR image in all three axes separately.
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