Viren Amin

Ultrasound Image Texture Analysis for Characterizing Intramuscular Fat Content of Live Beef Cattle

The primary factors in determining beef quality grades are the amount and distribution of intramuscular fat percentage (IMFAT). Texture analysis was applied to ultrasound B-mode images from ribeye muscle of live beef cattle to predict its IMFAT. We used wavelet transform (WT) for multiresolutional texture analysis and second-order statistics using a gray-level co-occurrence matrix (GLCM) technique. Sets of WT-and GLCM-based texture features were calculated from ultrasonic images from 207 animals and linear regression methods were used for IMFAT prediction. WT-based features included energy ratios, central moments of wavelet-decomposed subimages and wavelet edge density. The regression model using WT features provided a root mean square error (RMSE) of 1.44 for prediction of IMFAT using validation images, while that of GLCM features provided an RMSE of 1.90. The prediction models using the WT features showed potential for objective quality evaluation in the live animals.

Tissue characterization for beef grading using texture analysis of ultrasonic images

The primary factors in determining beef quality grades are the amount and distribution (or marbling) of intramuscular fat. Under the current USDA Grading system, the quality is subjectively graded by certified inspectors. There is a growing demand in the meat industry for an objective system of evaluating the quality of beef carcasses as well as live animals. A real-time ultrasound technique was used to characterize intramuscular fat in the longissimus dorsi (rib-eye) muscle of 126 live animals. Two approaches of B-mode image texture analysis, namely spacial gray-level dependence matrices and gray-level run-length matrices, were used. The significant texture parameters were used to develop models for predicting intramuscular %fat. With validation testing of these models, from more than 75 percent of the images, the %fat values were predicted to within 1.5 percentage and from about 68 percent of the images, the %fat was predicted to within one percent. The preliminary results showed a good potential of ultrasound and texture analysis for tissue characterization and objectively evaluating beef quality

Non-invasive detection of fatty liver in dairy cows by digital analyses of hepatic ultrasonograms.

During early lactation, many dairy cows develop fatty liver, which is associated with decreased health and reproductive performance. Currently, fatty liver can be detected reliably only by using liver biopsy followed by chemical or histological analysis, which is not practical in most on-farm situations. We tested whether digital analyses of hepatic ultrasonograms can be used to detect non-invasively fatty liver and estimate liver triacylglycerol content. A total of 49 liver biopsies and ultrasonograms were taken from 29 dairy cows within 2 weeks postpartum. The usefulness of 17 first- or second-order parameters from digital analysis of B-mode ultrasonograms were evaluated by discriminant, correlation, and regression analyses. A group of linear combinations of the 17 parameters correctly classified 40 of 49 samples into normal liver as well as mild, moderate and severe fatty liver when cut-off values were 1%, 5% and 10% and correctly classified 45 of 49 samples when cut-off values were 5% and 10% triacylglycerol of wet weight. A linear combination of 16 image parameters estimated triacylglycerol concentrations of 38 of the 39 liver samples below the cut-off value of 10% within 2.5% of liver wet weight, and a linear combination of 3 parameters estimated triacylglycerol concentrations of the 10 liver samples above the cut-off value of 10% within 2% of liver wet weight. Therefore, ultrasound imaging followed by digital analysis of sonograms has potential to non-invasively detect fatty liver and estimate liver triacylglycerol content.

Therapy planning and monitoring of tissue ablation by high intensity focused ultrasound (HIFU) using imaging and simulation

High intensity focused ultrasound (HIFU) “cooks” or ablates the target tissue at the focus of the ultrasound beam by thermal and cavitation effects. The HIFU is emerging as a non-invasive method for tumor ablation. The HIFU application for tissue ablation requires tools for dosimetry therapy planning, and real-time feedback of the intended and actual target tissues. Pretreatment planning is an important step for a successful HIFU therapy outcome. Typically, the therapy planning approach involves the use of pretreatment imaging data, defining the target and surrounding tissues by manual or semiautomatic segmentation, development of a 3-D anatomy model of the region of interest from segmentation or registration with a reference dataset, simulation of the HIFU beam and thermal dosimetry around the target tissue, display and 3-D visualization of imaging and simulation data, and review of the treatment plan options. Recent developments in therapy planning using imaging are targeted for specific applications such as prostate cancer using 3-D ultrasound images and uterine fibroids using MRI. However, significant developments have been accomplished in image guidance and feedback during the delivery of HIFU treatments. This talk reviews recent work towards therapy planning and presents approaches for developing strategies for HIFU therapy. It describes general and target-specific techniques and software tools for HIFU treatment planning using pretherapy imaging, and monitoring and controlling the HIFU delivery and tissue lesion using 1D, 2D and 3D ultrasound imaging. This aids development of optimized, high-precision HIFU applications for a controlled ablation of the target tumor. It also potentially reduces the overall treatment duration and exposure to non-target tissues.

Ultrasound Tissue Characterization for Quality Grading of Beef Carcasses

In the Unites States, beef carcasses are subjectively graded by certified inspectors from the United States Department of Agriculture (USDA). The primary factors in determining beef quality grades are the amount and distribution (or marbling) of intramuscular fat. The intramuscular fat level is estimated by visual inspection of texture pattern in a cross-sectional area of the Longissimus dorsi (ribeye) muscle between 12th and 13th ribs. The four primary grades, from high to low marbling, are Prime, Choice, Select, and Standard. There is a growing demand in the meat industry for an objective system of evaluating the quality of beef carcasses as well as live animals. With some sort of instrument grading system, the beef industry could move towards a long desired goal of value-based marketing.

An Interactive HIFU Therapy Planning Using Simulation & Visualization

Planning of HIFU therapy using patient‐specific data is crucial for successful results. We are developing integrated tools for HIFU therapy planning using pre‐treatment imaging, HIFU simulation, and interactive visualization. We employ techniques for 2D/3D image segmentation to generate layered surface model; ultrasound simulation of beam intensity distribution and HIFU temperature profiles; visualization of integrated 3D anatomy and US beam simulation; and interactive strategy planning for studying the approaches of HIFU delivery. We present a systematic approach for developing and integrating these tools in interactive software using C++, OpenGL, C♯.Net, and ITK. With interactive visualization of the HIFU simulation parameters and the tissue effects, a range of scenario could be studied for an optimal HIFU delivery for a given patient. This continuing work has potential to aid development of optimized high‐precision HIFU dosimetry and patient‐specific planning strategies by reducing the guess work on do...

HIFU Therapy Planning Using Pre‐treatment Imaging and Simulation

Current HIFU challenges include amount of tissue that can be destroyed by a single exposure, the inability to treat through bone, difficulty in monitoring therapy in real‐time, and difficulty in planning the strategy before therapy. Technological advances such as multi‐transducer or array beam generator, instrumentation and image‐based guidance of HIFU treatment promise to overcome many of these problems. However, there is limited work toward HIFU dosimetry and therapy planning. We present a systematic approach for developing pre‐treatment planning and HIFU dose calculations for specific target location using simulations and imaging data. We also present initial techniques and tools towards HIFU treatment planning (targeted for open‐skull brain tumor therapy) using patient‐specific pre‐therapy imaging (e.g., CT or MRI) similar to dosimetry and planning for radiation therapy. This work has potential to aid development of optimized high‐precision HIFU dosimetry and patient‐specific planning strategies for c...

Ultrasonic image processing for tendon injury evaluation

Image texture analysis techniques have been applied for evaluating tendon injuries in racehorses. Ultrasound images from superficial and deep digital flexor tendons have been characterized and a measure for quantifying injury grade has been proposed. Wavelet-based texture segmentation and classification algorithms have been developed for quantification of the injury grades. Discrete wavelet packet frames and standard discrete wavelet transforms are used to measure the percentage of the tendon injury and tendon fiber alignment, respectively. Results demonstrating the effectiveness of the approach in predicting the percentage of the tendon injury as well as the degree of tendon fiber alignment are presented.

Texture Analysis Using Multiresolution Analysis for Ultrasound Tissue Characterization

There is a growing demand in the meat industry for a quantitative method of grading beef carcasses. Commercially available beef in the United States is graded subjectively by-certified United States Department of Agriculture (USDA) inspectors. This is done by visually determining the amount and distribution of intramuscular fat (IMFAT) or marbling in the ribeye muscle. A method for estimating quality attributes (such as marbling) in live animals would help cluster feedlot cattle into outcome groups for more effective marketing.

Application of A-Mode Ultrasound to Characterize Intramuscular Fat Content

Intramuscular fat content and distribution (marbling) are important attributes for beef quality grading. The USDA (United States Department of Agriculture) certified inspectors determine the beef quality grades, based on marbling, by visually inspecting the cross sections of longissimus dorsi (ribeye) muscle at the 12th rib location on chilled beef carcass. This subjective method of grading, however, will not meet the meat industry’s demand for a value based marketing system. One important step towards this goal is an objective method of characterizing intramuscular fat or marbling. B-mode ultrasound has been shown to have the potential for predicting intramuscular percentage fat (%-fat) in live animals [1] as well as carcasses [2]. This paper presents the potential of A-mode ultrasound for characterizing intramuscular fat.