Image analysis – Image enhancement or restoration – Image filter
Reexamination Certificate
1998-04-14
2001-01-09
Rogers, Scott (Department: 2724)
Image analysis
Image enhancement or restoration
Image filter
C382S132000, C382S172000, C382S194000, C382S199000, C382S261000, C382S264000, C382S266000
Reexamination Certificate
active
06173083
ABSTRACT:
TECHNICAL FIELD
This invention relates to the processing of discrete picture element or pixel images, and, more particularly, to a technique for automatically identifying and enhancing certain structural or salient features defined by pixels in such images. The technique is particularly suitable for medical imaging systems and modalities, such as magnetic resonance imaging.
BACKGROUND ART
Various techniques have been developed for acquiring and processing discrete pixel image data. Discrete pixel images are composed of an array or matrix of pixels having varying properties, such as intensity, color and so on. The data defining each pixel may be acquired in various manners, depending upon the imaging modality employed. Modalities in medical imaging, for example, include magnetic resonance imaging techniques, X-ray techniques, and so forth. In general, however, each pixel is represented by a signal, typically a digitized value representative of a sensed parameter, such as an emission of material excited within each pixel region or radiation received within each pixel region. To facilitate interpretation of the image, the pixel values must be filtered and processed to enhance definition of features of interest to an observer. Ultimately, the processed image is reconstituted for display or printing.
Various techniques have been employed for enhancing discrete pixel images to facilitate their interpretation. Such techniques may employ identification of contrast regions, edges, and so forth, as defined by series of pixels or groups of pixels within the image matrix. Smoothing and sharpening steps may be employed for bringing out certain edges or contrast regions, or for de-emphasizing specific areas not considered of interest.
However, heretofore known techniques do not always provide a satisfactory degree of flexibility or computational efficiency. In particular, existing techniques may require operator intervention in defining salient structures, sometimes requiring processing of raw data several times based on operator adjustments before arriving at an acceptable final image. Moreover, where variations in image signal acquisition, processing and display circuitry between systems and between images in a single system result in corresponding variations in relationships between the pixels defining an image, structures of interest within a subject may not be consistently sensed, processed and displayed. Consequently, structures, textures, contrasts and other image features may be difficult to visualize and compare both within single images and between a set of images. As a result, attending physicians or radiologists presented with the images may experience difficulties in interpreting the relevant structures.
DISCLOSURE OF THE INVENTION
The invention provides a technique for identifying salient structures in discrete pixel images. In an exemplary embodiment, the technique makes use of gradient data generated for each pixel to automatically determine a gradient threshold used to separate structural features in the resulting image from non-structural features. Parameters employed in the selection of the gradient threshold for definition of image structures may be set or altered by an operator, or may rely upon default values, thereby providing both flexibility and, where desired, reducing the need for operator intervention. Parameters used to define the image structure may also be varied depending upon the matrix size of the image. The technique also facilitates the separation of small, noisy regions from the definition of image structure. Such regions are identified in a computationally efficient manner, and their size may be defined by default values or by values selected by an operator. The resulting structural definition may then be further enhanced through smoothing and sharpening processes. The technique may be applied to a wide range of image types acquired from various imaging modalities.
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Cabou Christian G.
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General Electric Company
Price Phyllis Y.
Rogers Scott
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