Depth recovery of hairy fibers for precise yarn hairiness measurement.

Hairiness is a concept describing the amount of hairy fibers (hairs) protruding from a yarn core in different spatial orientations and shapes. Most image-based hairiness assessment methods measure hairs by projecting a yarn on a 2D image plane, which suffers from two major problems: 1) not detecting defocused hairs (fuzzy hairs) when hairs are out of the field of view of the imaging system and 2) miscalculating real lengths of spatially curved hairs. The objective of this research was to develop a new image-based hairiness measurement method to mitigate these problems. The proposed method included two tasks: yarn image segmentation and hairiness assessment. The first task was to improve the detection rate of fuzzy hairs with a hybrid algorithm combining double homomorphic filtering and region-growing algorithms. The second task was to establish a width-depth mapping model for defocused hairs to compensate measurable lengths of defocused hairs based on their width information. The experiment results demonstrated that the proposed segmentation algorithm can detect fuzzy hairs usually missed by the previously used algorithm, and can produce more accurate hair length measurements than the previous algorithm when compared to the corresponding manual measurements, which were considered as the gold standard in this study.

Rapid acquisition of high-volume microscopic images using predicted focal plane.

For an automated microscopic imaging system, the image acquisition speed is one of the most critical performance features because many applications require to analyse high-volume images. This paper illustrates a novel approach for rapid acquisition of high-volume microscopic images used to count blood cells automatically. This approach firstly forms a panoramic image of the sample slide by stitching sequential images captured at a low magnification, selects a few basic points (x, y) indicating the target areas from the panoramic image, and then refocuses the slide at each of the basic points at the regular magnification to record the depth position (z). The focusing coordinates (x, y, z) at these basic points are used to calculate a predicted focal plane that defines the relationship between the focus position (z) and the stage position (x, y). Via the predicted focal plane, the system can directly focus the objective lens at any local view, and can tremendously save image-acquisition time by avoiding the autofocusing function. The experiments showed how to determine the optimal number of the basic points at a given imaging condition, and proved that there is no significant difference between the images captured using the autofocusing function or the predicted focal plane.

Automated quantification of abdominal adiposity by magnetic resonance imaging.

OBJECTIVES: To develop a fully-automated algorithm to process axial magnetic resonance imaging (MRI) slices for quantifying abdominal visceral, subcutaneous and total adipose tissues, i.e., VAT, SAT, and TAT, without human intervention or prior knowledge. MATERIALS AND METHODS: Fat regions in single MRI slice or sequence (20 slices) were identified with image processing techniques including region-growing, inhomogeneity correction, fuzzy c-means clustering, and active contours segmentation. The MR images of 85 subjects (60 males and 25 females), whose body mass index (BMI) values ranged from 19.96 to 40.35 kg/m2 , were analyzed using the fully-automated algorithm-the automatic method developed in the research and the widely used semi-automated software (sliceOmatic® Tomovision, Inc.)-the reference method. RESULTS: The proposed automated method showed good performance against the reference method to quantify adipose tissues in both single umbilical slice and MRI sequence. The square of the Pearson correlation coefficients (R2 ) based on the results generated from the two methods for VAT/SAT/TAT were 0.977/0.998/0.997 for single slice data and 0.995/0.999/0.999 for volumetric data. The intra-class correlation of visceral adipose tissue (VAT) between the three operators was 0.939 in the reference method, which was improved to 0.999 in the automatic method. The adipose tissue measurements in the slice at Lumbar 3 vertebra have the highest correlation with the total fat volumes across the entire abdomen. CONCLUSION: The fully-automated algorithm presented in the paper provides an accurate and reliable assessment of abdominal fat without human intervention. Am. J. Hum. Biol. 28:757-766, 2016. © 2016Wiley Periodicals, Inc.

Prediction of Android and Gynoid Body Adiposity via a Three-dimensional Stereovision Body Imaging System and Dual-Energy X-ray Absorptiometry.

OBJECTIVE: Current methods for measuring regional body fat are expensive and inconvenient compared to the relative cost-effectiveness and ease of use of a stereovision body imaging (SBI) system. The primary goal of this research is to develop prediction models for android and gynoid fat by body measurements assessed via SBI and dual-energy x-ray absorptiometry (DXA). Subsequently, mathematical equations for prediction of total and regional (trunk, leg) body adiposity were established via parameters measured by SBI and DXA. METHODS: A total of 121 participants were randomly assigned into primary and cross-validation groups. Body measurements were obtained via traditional anthropometrics, SBI, and DXA. Multiple regression analysis was conducted to develop mathematical equations by demographics and SBI assessed body measurements as independent variables and body adiposity (fat mass and percentage fat) as dependent variables. The validity of the prediction models was evaluated by a split sample method and Bland-Altman analysis. RESULTS: The R(2) of the prediction equations for fat mass and percentage body fat were 93.2% and 76.4% for android and 91.4% and 66.5% for gynoid, respectively. The limits of agreement for the fat mass and percentage fat were -0.06 ± 0.87 kg and -0.11% ± 1.97% for android and -0.04 ± 1.58 kg and -0.19% ± 4.27% for gynoid. Prediction values for fat mass and percentage fat were 94.6% and 88.9% for total body, 93.9% and 71.0% for trunk, and 92.4% and 64.1% for leg, respectively. CONCLUSIONS: The three-dimensional (3D) SBI produces reliable parameters that can predict android and gynoid as well as total and regional (trunk, leg) fat mass.

Efficacy of thigh volume ratios assessed via stereovision body imaging as a predictor of visceral adipose tissue measured by magnetic resonance imaging.

OBJECTIVES: The research examined the efficacy of regional volumes of thigh ratios assessed by stereovision body imaging (SBI) as a predictor of visceral adipose tissue measured by magnetic resonance imaging (MRI). Body measurements obtained via SBI also were utilized to explore disparities of body size and shape in men and women. METHOD: One hundred twenty-one participants were measured for total/regional body volumes and ratios via SBI and abdominal subcutaneous and visceral adipose tissue areas by MRI. RESULTS: Thigh to torso and thigh to abdomen-hip volume ratios were the most reliable parameters to predict the accumulation of visceral adipose tissue depots compared to other body measurements. Thigh volume in relation to torso [odds ratios (OR) 0.44] and abdomen-hip (OR 0.41) volumes were negatively associated with increased risks of greater visceral adipose tissue depots, even after controlling for age, gender, and body mass index (BMI). Irrespective of BMI classification, men exhibited greater total body (80.95L vs. 72.41L), torso (39.26L vs. 34.13L), and abdomen-hip (29.01L vs. 25.85L) volumes than women. Women had higher thigh volumes (4.93L vs. 3.99L) and lower-body volume ratios [thigh to total body (0.07 vs. 0.05), thigh to torso (0.15 vs. 0.11), and thigh to abdomen-hip (0.20 vs. 0.15); P < 0.05]. CONCLUSIONS: The unique parameters of the volumes of thigh in relation to torso and abdomen-hip, by SBI were highly effective in predicting visceral adipose tissue deposition. The SBI provided an efficient method for determining body size and shape in men and women via total and regional body volumes and ratios. Am. J. Hum. Biol. 27:445-457, 2015. © 2015 Wiley Periodicals, Inc.

Validation of a 3-dimensional laser body scanner for assessment of waist and hip circumference.

OBJECTIVES: To evaluate the reliability and validity of a 3-dimensional laser body scanner for estimation of waist and hip circumferences and waist:hip ratio. METHODS: Seventy women were evaluated for waist and hip circumference and waist:hip ratio via laser scanner and tape measure. In a subset of 34 participants, 8 repeated measures of laser scanning were performed for reproducibility analysis. Validity of the instrument was assessed by regression and Bland-Altman comparison of measures of waist and hip circumferences and waist:hip ratio to tape measure. RESULTS: Reproducibility analysis showed little difference between within-subjects measurements of circumferences (intraclass correlation coefficient ≥0.992, p < 0.01). Evaluation of waist and hip circumferences measured by body scanning did not differ significantly from tape measure (p > 0.05). Bland-Altman analysis showed no bias between laser scanning and tape measure. CONCLUSION: These findings indicate that the 3-dimensional laser body scanner is a reliable and valid technique for the estimation of waist and hip circumferences as compared with tape measure. This instrument is promising as a quick and simple method of body circumference analysis.

A Portable Stereo Vision System for Whole Body Surface Imaging.

This paper presents a whole body surface imaging system based on stereo vision technology. We have adopted a compact and economical configuration which involves only four stereo units to image the frontal and rear sides of the body. The success of the system depends on a stereo matching process that can effectively segment the body from the background in addition to recovering sufficient geometric details. For this purpose, we have developed a novel sub-pixel, dense stereo matching algorithm which includes two major phases. In the first phase, the foreground is accurately segmented with the help of a predefined virtual interface in the disparity space image, and a coarse disparity map is generated with block matching. In the second phase, local least squares matching is performed in combination with global optimization within a regularization framework, so as to ensure both accuracy and reliability. Our experimental results show that the system can realistically capture smooth and natural whole body shapes with high accuracy.

Evaluation of a rotary laser body scanner for body volume and fat assessment.

This paper reports the evaluation tests on the reliability and validity of a 3-dimensional (3D) laser body scanner for estimation of body volume and % fat. Repeated measures of body imaging were performed for reproducibility analysis. Validity of the instrument was assessed by comparison of measures of body volume by imaging to hydrodensitometry, and body fat was compared to hydrodensitometry and dual energy X-ray absorptiometry. Reproducibility analysis showed little difference between within-subjects measurements of volume (ICC ≥ 0.99, p < 0.01). Body volume estimations by laser body scanner and hydrodensitometry were strongly related (r = 0.99, p < 0.01), and agreement was high (ICC = 0.99, p < 0.01). Measurements of % body fat also agreed strongly with each other between methods (ICC = 0.86, p < 0.01), and mean % fat estimates by body imaging did not differ from criterion methods (p > 0.05). These findings indicate that the 3D laser body scanner is a reliable and valid technique for the estimation of body volume. Furthermore, body imaging is an accurate measure of body fat, as compared to dual energy X-ray absorptiometry. This new instrument is promising as a quick, simple to use, and inexpensive method of body composition analysis.

Three-dimensional surface imaging system for assessing human obesity.

The increasing prevalence of obesity suggests a need to develop a convenient, reliable, and economical tool for assessment of this condition. Three-dimensional (3-D) body surface imaging has emerged as an exciting technology for the estimation of body composition. We present a new 3-D body imaging system, which is designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology is used to satisfy the requirement for a simple hardware setup and fast image acquisition. The portability of the system is created via a two-stand configuration, and the accuracy of body volume measurements is improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3-D body imaging. Body measurement functions dedicated to body composition assessment also are developed. The overall performance of the system is evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.

Fiber-Content Measurement of Wool-Cashmere Blends Using Near-Infrared Spectroscopy.

Cashmere and wool are two protein fibers with analogous geometrical attributes, but distinct physical properties. Due to its scarcity and unique features, cashmere is a much more expensive fiber than wool. In the textile production, cashmere is often intentionally blended with fine wool in order to reduce the material cost. To identify the fiber contents of a wool-cashmere blend is important to quality control and product classification. The goal of this study is to develop a reliable method for estimating fiber contents in wool-cashmere blends based on near-infrared (NIR) spectroscopy. In this study, we prepared two sets of cashmere-wool blends by using either whole fibers or fiber snippets in 11 different blend ratios of the two fibers and collected the NIR spectra of all the 22 samples. Of the 11 samples in each set, six were used as a subset for calibration and five as a subset for validation. By referencing the NIR band assignment to chemical bonds in protein, we identified six characteristic wavelength bands where the NIR absorbance powers of the two fibers were significantly different. We then performed the chemometric analysis with two multilinear regression (MLR) equations to predict the cashmere content (CC) in a blended sample. The experiment with these samples demonstrated that the predicted CCs from the MLR models were consistent with the CCs given in the preparations of the two sample sets (whole fiber or snippet), and the errors of the predicted CCs could be limited to 0.5% if the testing was performed over at least 25 locations. The MLR models seem to be reliable and accurate enough for estimating the cashmere content in a wool-cashmere blend and have potential to be used for tackling the cashmere adulteration problem.

Novel Body Shape Descriptors for Abdominal Adiposity Prediction Using Magnetic Resonance Images and Stereovision Body Images.

OBJECTIVE: The purpose of this study was to design novel shape descriptors based on three-dimensional (3D) body images and to use these parameters to establish prediction models for abdominal adiposity. METHODS: Sixty-six men and fifty-five women were recruited for abdominal magnetic resonance imaging (MRI) and 3D whole-body imaging. Volumes of abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were measured from MRI sequences by using a fully automated algorithm. The shape descriptors were measured on the 3D body images by using the software developed in this study. Multiple regression analysis was employed on the training data set (70% of the total participants) to develop predictive models for VAT and SAT, with potential predictors selected from age, BMI, and the body shape descriptors. The validation data set (30%) was used for the validation of the predictive models. RESULTS: Thirteen body shape descriptors exhibited high correlations (P < 0.01) with abdominal adiposity. The optimal predictive equations for VAT and SAT were determined separately for men and women. CONCLUSIONS: Novel body shape descriptors defined on 3D body images can effectively predict abdominal adiposity quantified by MRI.

Validation study of a Kinect based body imaging system.

BACKGROUND: Understanding the reliability and precision of the data obtained using three-dimensional body scanners is very important if it is intended to replace the traditional data collection methods. If the collection of anthropometric data with three-dimensional body scanners is a fast and reliable process that produces precise data at a low price, it could be used for numerous applications worldwide. Many studies have addressed data collected by white light and laser based scanners. OBJECTIVE: This study provides a comparative analysis between the anthropometric data collected using a Kinect body imaging system with the data collected using traditional manual methods. Moreover, a comparison is also made between the results obtained in this study and the results of previous studies of different types of body scanners. METHODS: The Mean Absolute Difference was calculated and all the values were compared to the maximum allowable error defined in ISO 20685. Additionally, an analysis of the significant differences between the two acquisition methods was also applied to a physical mannequin, to understand how the body movement and body stance variation in human participants impacts the results obtained. RESULTS: There are few body measurements that are close to this restricted allowable error. The results were better when the mannequin was measured. Although they were still above the ISO 20685 limit, they were much closer than the results obtained for human participants. CONCLUSION: The main cause of the differences between the two methods is the time required for the 3D system to acquire the data. The involuntary body sway of human participants is more difficult to control when the time span is too long.

Predictive equations for central obesity via anthropometrics, stereovision imaging and MRI in adults.

OBJECTIVE: Abdominal visceral adiposity is related to risks for insulin resistance and metabolic perturbations. Magnetic resonance imaging (MRI) and computed tomography are advanced instruments that quantify abdominal adiposity; yet field use is constrained by their bulkiness and costliness. The purpose of this study is to develop prediction equations for total abdominal, subcutaneous, and visceral adiposity via anthropometrics, stereovision body imaging (SBI), and MRI. METHODS: Participants (67 men and 55 women) were measured for anthropometrics and abdominal adiposity volumes evaluated by MRI umbilicus scans. Body circumferences and central obesity were obtained via SBI. Prediction models were developed via multiple linear regression analysis, utilizing body measurements and demographics as independent predictors, and abdominal adiposity as a dependent variable. Cross-validation was performed by the data-splitting method. RESULTS: The final total abdominal adiposity prediction equation was -470.28 + 7.10 waist circumference - 91.01 gender + 5.74 sagittal diameter (R2 = 89.9%), subcutaneous adiposity was -172.37 + 8.57 waist circumference - 62.65 gender - 450.16 stereovision waist-to-hip ratio (R2 =90.4%), and visceral adiposity was -96.76 + 11.48 central obesity depth - 5.09 central obesity width + 204.74 stereovision waist-to-hip ratio - 18.59 gender (R2 = 71.7%). R2 significantly improved for predicting visceral fat when SBI variables were included, but not for total abdominal or subcutaneous adiposity. CONCLUSIONS: SBI is effective for predicting visceral adiposity and the prediction equations derived from SBI measurements can assess obesity.

Mechanical properties of small-diameter polyurethane vascular grafts reinforced by weft-knitted tubular fabric.

Polyester filament yarns of different Deniers were knitted into tubular fabrics with different densities and thicknesses on a specially designed weft-knitting machine. The developed tubular fabric was used to reinforce polyurethane vascular graft and thus a kind of composite vascular graft was fabricated with a small inner diameter of 4 mm. Tensile properties of the reinforced composite vascular grafts were compared with the control tubular fabric and the pure PU vascular grafts. Elasticity and strength of the reinforced vascular grafts were improved compared with the weft-knitted tubular fabrics. Strength of the reinforced composite vascular grafts was almost 5-10 times of the strength of the pure PU vascular grafts. As the PU content increased in the reinforced composite vascular grafts, the wall thickness of the vascular graft and its strength increased, but the initial modulus of the reinforced composite vascular grafts remained similar to that of the weft-knitted tubular fabric, and the PU content showed little influence on the initial modulus of the reinforced composite vascular grafts. Microporous structure can also be fabricated in the wall of the reinforced composite vascular grafts.