Lior Shamir1. 1. Lawrence Technological University, 21000 W Ten Mile Rd., Southfield, MI 48075, USA. lshamir@mtu.edu
Abstract
PURPOSE: To develop an image analysis method that can automatically find correlations between a set of plain radiographs and continuous clinical or physiological indicators. METHODS: Knee X-rays taken from the Baltimore Longitudinal Study of Aging are used in this study. The computer analysis method is based on the WND-CHARM image feature set filtered by using the Pearson correlation of each feature with the continuous variable, and the estimated value is determined by a weighted nearest neighbor interpolation. RESULTS: Experimental results using 300 radiographs show that the proposed method can correlate knee X-rays with physiological indicators such as sex, age, height, weight, and BMI. For instance, the Pearson correlation between the X-ray images and the height and weight were 0.59 and 0.62, respectively. CONCLUSIONS: Using computer analysis, X-ray images can be correlated to continuous physiological variables that might not have a direct and straightforward link to the visual content of the radiograph. This approach of radiology image analysis can be used in population studies for detecting biomarkers and also in genome-wide association studies for studying the link between genes and anatomy.
PURPOSE: To develop an image analysis method that can automatically find correlations between a set of plain radiographs and continuous clinical or physiological indicators. METHODS: Knee X-rays taken from the Baltimore Longitudinal Study of Aging are used in this study. The computer analysis method is based on the WND-CHARM image feature set filtered by using the Pearson correlation of each feature with the continuous variable, and the estimated value is determined by a weighted nearest neighbor interpolation. RESULTS: Experimental results using 300 radiographs show that the proposed method can correlate knee X-rays with physiological indicators such as sex, age, height, weight, and BMI. For instance, the Pearson correlation between the X-ray images and the height and weight were 0.59 and 0.62, respectively. CONCLUSIONS: Using computer analysis, X-ray images can be correlated to continuous physiological variables that might not have a direct and straightforward link to the visual content of the radiograph. This approach of radiology image analysis can be used in population studies for detecting biomarkers and also in genome-wide association studies for studying the link between genes and anatomy.
Authors: Selvon F St Clair; Carlos Higuera; Viktor Krebs; Nabil A Tadross; Jerrod Dumpe; Wael K Barsoum Journal: Clin Geriatr Med Date: 2006-08 Impact factor: 3.076
Authors: I Boniatis; L Costaridou; D Cavouras; I Kalatzis; E Panagiotopoulos; G Panayiotakis Journal: Med Biol Eng Comput Date: 2006-08-15 Impact factor: 2.602