ArticleJBMR plus2026
Evaluation of the use of segmentation-based and deconvolution-based three-dimensional joint space width analysis of the hand and wrist.
Article in JBMR plus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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5 authors.
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Abstract
Three-dimensional morphometric analyses of joint space from CT scans can provide a quantitative and unbiased evaluation of radiographic damage from arthritis. This potentially offers greater sensitivity for disease assessment and monitoring than traditional ordinal scoring systems. Previously established methods for 3-dimensional joint space analysis from CT scans can be categorized into segmentation-based and grayscale deconvolution-based methods. However, segmentation-based methods have not been employed for joints other than metacarpophalangeal joints, nor have they been compared to deconvolution-based methods. This study compared the joint space width (JSW) distribution from various hand and wrist joints in photon-counting CT images, using both measurement approaches. From these distributions, the mean (JSW.Mean), standard deviation (JSW.SD), maximum (JSW.Max), minimum (JSW.Min), 95th percentile (JSW.95%), and fifth percentile (JSW.5%) values were calculated. For each morphometry parameter, agreement between the 2 methods was assessed by calculating the coefficient of determination (R
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