An automated, parallel processing approach to biomolecular sample preparation

Sample preparation for DNA and RNA assays is a prime candidate for laboratory automation. A novel, parallel processing device that performs the three separate liquid-handling functions necessary for such sample preparation-dispensing, pipetting, and pressurizing-is presented. The device comprises an array of fine nozzles connected by fluidic channels to automatically and precisely distribute flow between one source and an array of points. The design principles, as well as the experimental and computational methods used to develop the device, are described. Test results, including accuracy, uniformity, volume range, and timing, are presented. The functionality of the device is demonstrated by performing a solid-phase extraction of DNA with two types of microcolumns.     

A framework for weighted fusion of multiple statistical models of shape and appearance

This paper presents a framework for weighted fusion of several active shape and active appearance models. The approach is based on the eigenspace fusion method proposed by Hall et al., which has been extended to fuse more than two weighted eigenspaces using unbiased mean and covariance matrix estimates. To evaluate the performance of fusion, a comparative assessment on segmentation precision as well as facial verification tests are performed using the AR, EQUINOX, and XM2VTS databases. Based on the results, it is concluded that the fusion is useful when the model needs to be updated online or when the original observations are absent     

Database Structure and Manipulation Capabilities of a Picture Database Management System (PICDMS)

The database structure and data manipulation capabilities of a generalized PICture Database Management System (PICDMS) are presented. They are based on a dynamic, stacked-image, logical database structure that uses gridded, rather than topological, data representation. A prototype PICDMS has been designed and implemented. A commercial version is being used as a generator of image processing programs. The system has novel capabilities for nonprogrammer users: it is able to 1) build multiple-variable databases from photographs and other two-dimensional data sources such as maps, drawings, etc., and 2) manipulate such data using simple logical commands. Physical organization and accessing strategies are outlined. A summary of the PICDMS data manipulation capabilities is presented and a subset of operations is illustrated with brief examples. A comprehensive example displays PICDMS capabilities and the programming advantages it possesses over other approaches.     

Automatic detection and quantification of tree-in-bud (TIB) opacities from CT scans

This study presents a novel computer-assisted detection (CAD) system for automatically detecting and precisely quantifying abnormal nodular branching opacities in chest computed tomography (CT), termed tree-in-bud (TIB) opacities by radiology literature. The developed CAD system in this study is based on 1) fast localization of candidate imaging patterns using local scale information of the images, and 2) M?bius invariant feature extraction method based on learned local shape and texture properties of TIB patterns. For fast localization of candidate imaging patterns, we use ball-scale filtering and, based on the observation of the pattern of interest, a suitable scale selection is used to retain only small size patterns. Once candidate abnormality patterns are identified, we extract proposed shape features from regions where at least one candidate pattern occupies. The comparative evaluation of the proposed method with commonly used CAD methods is presented with a dataset of 60 chest CTs (laboratory confirmed 39 viral bronchiolitis human parainfluenza CTs and 21 normal chest CTs). The quantitative results are presented as the area under the receiver operator characteristics curves and a computer score (volume affected by TIB) provided as an output of the CAD system. In addition, a visual grading scheme is applied to the patient data by three well-trained radiologists. Interobserver and observer-computer agreements are obtained by the relevant statistical methods over different lung zones. Experimental results demonstrate that the proposed CAD system can achieve high detection rates with an overall accuracy of 90.96%. Moreover, correlations of observer-observer (R(2)=0.8848, and observer-CAD agreements (R(2)=0.824, validate the feasibility of the use of the proposed CAD system in detecting and quantifying TIB patterns.     

Automatic identification of the pectoral muscle in mammograms

The pectoral muscle represents a predominant density region in most medio-lateral oblique (MLO) views of mammograms; its inclusion can affect the results of intensity-based image processing methods or bias procedures in the detection of breast cancer. Local analysis of the pectoral muscle may be used to identify the presence of abnormal axillary lymph nodes, which may be the only manifestation of occult breast carcinoma. We propose a new method for the identification of the pectoral muscle in MLO mammograms based upon a multiresolution technique using Gabor wavelets. This new method overcomes the limitation of the straight-line representation considered in our initial investigation using the Hough transform. The method starts by convolving a group of Gabor filters, specially designed for enhancing the pectoral muscle edge, with the region of interest containing the pectoral muscle. After computing the magnitude and phase images using a vector-summation procedure, the magnitude value of each pixel is propagated in the direction of the phase. The resulting image is then used to detect the relevant edges. Finally, a post-processing stage is used to find the true pectoral muscle edge. The method was applied to 84 MLO mammograms from the Mini-MIAS (Mammographic Image Analysis Society, London, U.K.) database. Evaluation of the pectoral muscle edge detected in the mammograms was performed based upon the percentage of false-positive (FP) and false-negative (FN) pixels determined by comparison between the numbers of pixels enclosed in the regions delimited by the edges identified by a radiologist and by the proposed method. The average FP and FN rates were, respectively, 0.58% and 5.77%. Furthermore, the results of the Gabor-filter-based method indicated low Hausdorff distances with respect to the hand-drawn pectoral muscle edges, with the mean and standard deviation being 3.84 +/- 1.73 mm over 84 images.     

Using perturbation theory to compute the morphological similarity of diffusion tensors

Computing the morphological similarity of diffusion tensors (DTs) at neighboring voxels within a DT image, or at corresponding locations across different DT images, is a fundamental and ubiquitous operation in the postprocessing of DT images. The morphological similarity of DTs typically has been computed using either the principal directions (PDs) of DTs (i.e., the direction along which water molecules diffuse preferentially) or their tensor elements. Although comparing PDs allows the similarity of one morphological feature of DTs to be visualized directly in eigenspace, this method takes into account only a single eigenvector, and it is therefore sensitive to the presence of noise in the images that can introduce error intothe estimation of that vector. Although comparing tensor elements, rather than PDs, is comparatively more robust to the effects of noise, the individual elements of a given tensor do not directly reflect the diffusion properties of water molecules. We propose a measure for computing the morphological similarity of DTs that uses both their eigenvalues and eigenvectors, and that also accounts for the noise levels present in DT images. Our measure presupposes that DTs in a homogeneous region within or across DT images are random perturbations of one another in the presence of noise. The similarity values that are computed using our method are smooth (in the sense that small changes in eigenvalues and eigenvectors cause only small changes in similarity), and they are symmetric when differences in eigenvalues and eigenvectors are also symmetric. In addition, our method does not presuppose that the corresponding eigenvectors across two DTs have been identified accurately, an assumption that is problematic in the presence of noise. Because we compute the similarity between DTs using their eigenspace components, our similarity measure relates directly to both the magnitude and the direction of the diffusion of water molecules. The favorable performance characteristics of our measure offer the prospect of substantially improving additional postprocessing operations that are commonly performed on DTI datasets, such as image segmentation, fiber tracking, noise filtering, and spatial normalization.     

Cooking tenderizing in beef

Heating tenderzes meat in three distinct phases. Up to 65°C aging occurs through proteolysis at specific sites in the myofibrils. From about 70°C the collagen of the connective tissue is denatured and melts. Above about 100°C the myofibrils begin to break down again presumably from non-specific high-temperature hydrolysis. The rate of cooking tenderizing above 70°C increases sharply with temperature and at 100°C is equal to the maximum aging rate at 60°C. However the collagen becomes more resistant to breakdown with animal age since the time to achieve maximum tenderizing of m. sternomandibularis at 80°C increases from 4 h for young calves to greater than 15 h for old bulls. There is little overlap in the temperature ranges of aging and cooking tenderizing above 70°C with a minimum tenderizing temperature of 67°C. The merits of tenderizing meat by holding it below or above this temperature are discussed.     

Computer-controlled mechanical simulation of the artificially ventilated human respiratory system

A mechanical lung simulator can be used to simulate specific lung pathologies, to test lung-function equipment, and in instruction. A new approach to mechanical simulation of lung behavior is introduced that uses a computer-controlled active mechatronic system. The main advantage of this approach is that the static and dynamic properties of the simulator can easily be adjusted via the control software. A nonlinear single-compartment mathematical model of the artificially ventilated respiratory system has been derived and incorporated into the simulator control system. This model can capture both the static and dynamic compliance of the respiratory system as well as nonlinear flow-resistance properties. Parameters in this model can be estimated by using data from artificially ventilated patients. It is shown that the simulation model fits patient data well. This mathematical model of the respiratory system was then matched to a model of the available physical equipment (the simulator, actuators, and the interface electronics) in order to obtain the desired lung behavior. A significant time delay in the piston motion control loop has been identified, which can potentially cause oscillations or even instability for high compliance values. Therefore, a feedback controller based on the Smith-predictor scheme was developed to control the piston motion. The control system, implemented on a personal computer, also includes a user-friendly interface to allow easy parameter setting.