摘要:
The present invention relates to a method for processing an image corresponding to a radiographic pattern, the image being formed of a plurality of pixels each having a value corresponding to density. The method includes the steps of obtaining an image corresponding to a radiographic pattern so that values of pixels forming the image are stored in a memory; dividing the image into a plurality of image regions based on the values of the pixels forming the image, each image region including pixels each of which has a value falling within a predetermined range; and applying an image processing to the plurality of image regions of the image, processing conditions used for the plurality of image regions in the image processing differing from each other.
摘要:
A method for improving the alignment accuracy between different medical images may be disclosed. A warped or non-warped previous image and a warped or non-warped current image may include a plurality of respective previous and current basic units, for example, pixels in a 2-dimensional image or voxels in a 3-dimensional image. To ensure accurate registration between the previous and current images, a first basic unit from the previous image may be replaced by a second basic unit from the current image if the value of the first and second basic units are identical or nearly identical. The first and second basic units may be selected from a nearly-identical region or “kernel” within the previous and current images.
摘要:
A method, system, computer readable medium and apparatus for computerized detection of lung nodules in computer tomography images, by which mask images are created such that subtractions of the mask image from a targeted CT section image reveal or highlight small lung nodules in the target CT section. The mask image is created utilizing the targeted CT section image along with other CT section images generated from the same CT scan. Based on these other section CT images and the targeted CT section image, a mask image can be created that is very similar to the target CT section image, but without the presence of small lung nodules. When the mask image is subtracted from the targeted CT section image, the differences between the mask images and the CT section images reveal small lung nodules. The mask image may be created by linear interpolation or a morphological filtered image.
摘要:
A method, system and computer readable medium for computerized processing of chest images including obtaining a digital first image of a chest (S100); producing a second image which is a mirror image (S300) of the first image; performing image warping on one of the first and second images to produce a warped image (S400) which is registered to the other of the first and second images; and subtracting the warped image from the other image to generate a subtraction image (S600). Another embodiment includes obtaining a digital first image of the chest of a subject; detecting ribcage edges on both sides of the lungs in the first chest image; determining average horizontal locations of the left and right ribcage edges at plural vertical locations; fitting the determined average horizontal locations to a straight line to derive a midline; rotating the chest image so that the midline is vertical; and shifting the rotated image to produce a lateral inclination corrected (S200) second image with the midline centered in the lateral inclination corrected image.
摘要:
A method, system and computer readable medium for a computer-automated method for identifying given image data, including obtaining template image data corresponding to said given image data; calculating correlation values between the given image data and said template image data; and identifying said image data based on the correlation values calculated in the calculating step.
摘要:
A computerized method for the detection and characterization of disease in an image derived from a chest radiograph, wherein an image in the chest radiograph is processed to determine the ribcage boundary, including lung top edges, right and left ribcage edges, and right and left hemidiaphragm edges. Texture measures including RMS variations of pixel values within regions of interest are converted to relative exposures and corrected for system noise existing in the system used to produce the image. Texture and/or geometric pattern indices are produced. A histogram(s) of the produced index (indices) is produced and values of the histograms) are applied as inputs to a trained artificial neural network, which classifies the image as normal or abnormal. In one embodiment, obviously normal and obviously abnormal images are determined based on the ratio of abnormal regions of interest to the total number of regions of interest in a rule-based method, so that only difficult cases to diagnose are applied to the artificial neural network.
摘要:
A method and system for automated analysis of digital radiographic images in which regions-of-interest (ROI's) are first determined, and subsequently analyzed for abnormalities. To locate the ROI's, the outer ribcage and midline boundary locations of the chest image are determined from the digital image data. Vertical profiles are then selected and background trend is then removed from each vertical profile. A shift-variant sinusoidal function is fitted to each vertical profile and ROI's are selected based on the fitted functions. The non-uniform background trend is removed from the original image data of each selected ROI to obtain corrected data. The power spectrum of the lung texture is obtained from the 2D Fourier transform of the corrected data and is filtered by the human visual response. Finally, the root-mean-square (rms) variation, R, and the first moment of the power spectrum, M, are determined as quantitative texture measures for the magnitude and coarseness (or fineness), respectively, of the lung texture.
摘要:
A method and system for automated classification of distinction between normal lungs and abnormal lungs with interstitial disease, based on the analysis of predetermined physical texture measures and also on a data base for normal lungs of these texture measures. The texture measures selected are the RMS variation, R, and the first moment of power spectrum, M, for lung texture. These two texture measures are normalized by using the data base for normal lungs. A single texture index is determined from the two normalized texture measures by taking into account the distribution (or the data base) of texture measures obtained from abnormal lungs, in order to facilitate the automated classification of normal and abnormal lungs. A threshold texture index is then chosen for initial selection of "abnormal" regions of interest (ROIs), which contain a large texture index above the threshold level. The selected abnormal ROIs are then subjected to three independent tests for a (1) definitely abnormal singular pattern, (2) localized abnormal pattern for two or more abnormal clustered ROIs, and (3) diffuse abnormal pattern for more than four abnormal ROIs distributed through the lung. A chest image containing any one of these abnormal patterns is classified as showing an abnormal lung with interstitial disease.
摘要:
A method of computerized analysis of temporally sequential digital images, including (a) determining first shift values between pixels of a first digital image and corresponding pixels of a second digital image; (b) warping the second digital image based on the first shift values to obtain a first warped image in which spatial locations of pixels are varied in relation to the first shift values; (c) determining second shift values between pixels of the first digital image and pixels of the first warped image; and (d) warping the first warped image based on the second shift values to obtain a second warped image in which spatial locations of pixels of the first warped image are varied in relation to the second shift values. Additional iterations of image warping are possible to enhance image registration between the first digital image and the warped version of the second digital image, followed by image subtraction of the first digital image and the final warped image to produce a difference image from which diagnosis of temporal changes ensues. Temporal subtraction assists radiologists in the detection of interval changes on chest radiographs, and particularly to overcome severe misregistration errors in the temporally sequential images mainly due to differences in a subject's inclination and/or rotation. In the production of shift values used in image warping, initial shift values are obtained by cross-correlation techniques using a template and search regions of interest. Shift vectors and a histogram of shift vectors in each lung are obtained from initial shift values. The histograms of shift vectors are used in the selection of sets of shift values for smoothing, using two-dimensional fitting and subsequent use of fitted shift values in image warping.
摘要:
A computerized method for the detection and characterization of disease in an image derived from a chest radiograph, wherein an image in the chest radiograph is processed to determine the ribcage boundary, including lung top edges, right and left ribcage edges, and right and left hemidiaphragm edges. Texture measures including RMS variations of pixel values within regions of interest are converted to relative exposures and corrected for system noise existing in the system used to produce the image. Texture and/or geometric pattern indices are produced. A histogram(s) of the produced index (indices) is produced and values of the histogram(s) are applied as inputs to a trained artificial neural network, which classifies the image as normal or abnormal. In one embodiment, obviously normal and obviously abnormal images are determined based on the ratio of abnormal regions of interest to the total number of regions of interest in a rule-based method, so that only difficult cases to diagnose are applied to the artificial neural network.