In dynamic radiological studies time-dependent processes, ranging from motion of the patient's own anatomical structures to the kinetics of a contrast agent or radiotracer, are recorded in a sequence of image fram...
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In dynamic radiological studies time-dependent processes, ranging from motion of the patient's own anatomical structures to the kinetics of a contrast agent or radiotracer, are recorded in a sequence of image frames. If the data are available in digital format, appreciation of regional patterns of behavior can be enhanced by digital operations on the image sequence. These operations can be considered as projecting out aspects of temporal behavior that are not readily or unambiguously perceptible to the unassisted observer. A report is presented on experiences with such functional images in three radiological modalities at the University of Wisconsin. Examples include nuclear medicine studies of the heart and liver, transmission computed tomography studies of the brain, and digital fluoroscopic studies of the heart and kidneys.
The problem of automatic registration of deformed images is addressed. It describes an iterative technique for gradually updating the local registration of two images based on a dynamic cooperative model. the method i...
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The problem of automatic registration of deformed images is addressed. It describes an iterative technique for gradually updating the local registration of two images based on a dynamic cooperative model. the method is cooperative in the sense that a feature at one location in an image influences decisions made at other locations. Initially, when registration is expected to be poor and feature measures unreliable, cooperative interaction is strong. It is progressively weakened with each iteration to permit matching of fine details. For a physical analogy, consider an elastic picture whose stiffness decreases with each iteration, and which is deformed by forces arising from similar features in another picture. Examples are shown for both dot patterns and gray-scale pictures.
An algorithm for finding the medial axis of an object in a 2-D binary picture has been developed. A set of real-valued boundary points for the object is extracted and smoothed using a linear combination of points in t...
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An algorithm for finding the medial axis of an object in a 2-D binary picture has been developed. A set of real-valued boundary points for the object is extracted and smoothed using a linear combination of points in the immediate neighborhood. A more detailed set of points is then defined by interpolation using a parabolic blending technique. To obtain the medial axis, circles are fitted for each point in the detailed set of points. Ech circle must be tangent to the point, be totally enclosed by the object and be of maximum size. The centers of these circles lie on the medial axis. The technique is especially suited to noisy data or coarsely sampled shapes.
image data compression can be achieved by a number of techniques such as DPCM and Transform Coding. Adaptive image compression can be done with any of these techniques. Adaptive image data compression is a procedure i...
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image data compression can be achieved by a number of techniques such as DPCM and Transform Coding. Adaptive image compression can be done with any of these techniques. Adaptive image data compression is a procedure in which the number of bits allocated to each image block changes from block to block depending on the block complexity. This variable input bit rate must be converted to a constant output bit rate by a rate buffer. A study is made of some causal and noncausal approaches to adaptively allocating bits under the constraint of a fixed size buffer. A discussion is also presented of the optimal noncausal approach whose performance is a least upper bound on any causal approach.
In order to carry out an automatic procedure to analyze a sequence of images and extract in that way the dynamic characteristics of the motion represented in the sequence, a certain number of methods are, at present, ...
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In order to carry out an automatic procedure to analyze a sequence of images and extract in that way the dynamic characteristics of the motion represented in the sequence, a certain number of methods are, at present, considered and evaluated by many authors. In that context one of the more interesting aspects consists in obtaining the segmentation of each frame that could be considered ″normalized″ in a given interval of frames belonging to the sequence. A method to obtain a normalized segmentation for the special case considered, is presented. The technique is based on the iterated application of a pair of algorithms the first of which is able to identify the moving parts and to make a check on the rightness of such identification;the second one carries out the ″normalization″ of frames of the sequence on the basis of the results furnished by the first algorithm.
A study was conducted to evaluate the usefulness of equal probability quantization as a preprocessing step in the automated interpretation of chest radiographs for pneumoconiosis. Nineteen chest radiograph pairs were ...
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A study was conducted to evaluate the usefulness of equal probability quantization as a preprocessing step in the automated interpretation of chest radiographs for pneumoconiosis. Nineteen chest radiograph pairs were analyzed. Each pair of radiographs consisted of a good quality film and a duplicate film on the same miner of acceptable but slightly poorer quality, as judged by two radiologists. The results of the study suggests that some reduction in the within subject variability of horizontal texture measurements can be obtained by preprocessing of the radiographs with equal probability quantization. This preprocessing step reduces the dependency of the texture measurements on film quality, although whether a corresponding improvement in classification accuracy can be obtained remains to be proven.
The problem of extending the scope of the recently developed concept of composite classifier systems to the domain of imperfectly supervised environments is considered in this study. The constraints underlying the ass...
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The problem of extending the scope of the recently developed concept of composite classifier systems to the domain of imperfectly supervised environments is considered in this study. The constraints underlying the associated problem of optimal partitioning of the feature space, for the case wherein the composite system consists of the linear and nearest neighbor (NN) classifiers, are appropriately reformulated taking into account the imperfectness of the training sample labels. The resulting constrained optimization problem is solved, as before, using SWIFT-Sequential Weight Increasing Factor Technique. The classical NN rule is also modified to give due weightage to the fact that the training samples are imperfectly labeled, thereby adapting the linear/NN composite classifier, in all its facets, for deployment in imperfectly supervised environments.
The shape number of a curve is derived for two-dimensional non-intersecting closed curves that are the boundary of simply connected regions. This description is independent of their size, orientation and position, but...
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The shape number of a curve is derived for two-dimensional non-intersecting closed curves that are the boundary of simply connected regions. This description is independent of their size, orientation and position, but it depends on their shape. Each curve carries ″within it″ its own shape number. The order of the shape number indicates the precision with which that number describes the shape of the curve. For a curve, the order of its shape number is the length of the perimeter of a 'discrete shape' (a closed curve formed by vertical and horizontal segments, all of equal length) closely corresponding to the curve. A procedure is given that deduces, without table look-up, string matching or correlations, the shape number of any order for an arbitrary curve.
In routine examination of chest radiographs, radiologists miss about 30% of the lung tumors in these pictures. To aid the radiologist in detecting these tumors the authors have designed and constructed, and are contin...
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In routine examination of chest radiographs, radiologists miss about 30% of the lung tumors in these pictures. To aid the radiologist in detecting these tumors the authors have designed and constructed, and are continuing to develop, a system consisting of a scanning microdensitometer, a digital minicomputer, a computer program, and a digital cathode-ray-tube color display. This system detects nodules in the range 5mm to 25mm mm and classifies them into two classes: tumor and nontumor. On a data base of 14 nodules in five radiographs, our system missed only one nodule and produced an average of seven false positives per radiograph.
Sequences of pictures of growing colonies of animal cells or microorganisms contain information useful to biologists. Special lighting increases the information contained in the pictures and decreases the difficulty o...
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Sequences of pictures of growing colonies of animal cells or microorganisms contain information useful to biologists. Special lighting increases the information contained in the pictures and decreases the difficulty of the image analysis. A high resolution flying spot scanner digitizes images of petri dishes recorded on film. Nonlinear edge region detectors and a region growing algorithm find the outlines of the colonies. Outlines which pass tests for validity are analyzed to extract further information. Data files of parameters are created which are analyzed by programs written by biologists. Statistical and other techniques were used to classify species and locate mutant colonies.
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