Abstract: A method of removing a potential false positive result in a stained sample. The method includes the steps of: acquiring a spectral image set of a stained sample; performing linear spectral unmixing of the spectral image set to obtain a plurality of rule images; calculating an error image for the stained sample; thresholding at least one of the plurality of rule images, wherein thresholding is based on the error image; and removing a potential false positive result from the at least one of the plurality of rule images based on thresholding.

Abstract: A method of presenting image data for elucidating morphology. The method includes the steps of: obtaining a spectral image data set of a sample, wherein the sample is labeled with a plurality of transmission stains; calculating a plurality of rule images from the spectral image data set; adjusting a level of intensity of one of the plurality of rule images independent of the other of the plurality of rule images; and presenting the plurality of rule images to a user.

Abstract: A method of removing a potential false positive result in a stained sample. The method includes the steps of: acquiring a spectral image set of a stained sample; performing linear spectral unmixing of the spectral image set to obtain a plurality of rule images; calculating an error image for the stained sample; thresholding at least one of the plurality of rule images, wherein thresholding is based on the error image; and removing a potential false positive result from the at least one of the plurality of rule images based on thresholding.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map may be segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map may be compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: A method and system for auto-focusing is disclosed where the number of the fractal pixels having a fractal dimension within a predetermined range is determined. The focused image is determined by adjusting the image to maximize the fractal pixel count. Alternatively, the focused image may be selected from a set of images, the image having the largest fractal pixel count selected as the focused image.

Abstract: A method and system for auto-focusing is disclosed where the number of the fractal pixels having a fractal dimension within a predetermined range is determined. The focused image is determined by adjusting the image to maximize the fractal pixel count. Alternatively, the focused image may be selected from a set of images, the image having the largest fractal pixel count selected as the focused image.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map may be segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map may be compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: A method for segmenting an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The image is segmented by thresholding the fractal map of the image.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map is segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map is compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: A method for segmenting an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The image is segmented by thresholding the fractal map of the image.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map is segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map is compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: A method and system for auto-focusing is disclosed where the number of the fractal pixels having a fractal dimension within a predetermined range is determined. The focused image is determined by adjusting the image to maximize the fractal pixel count. Alternatively, the focused image may be selected from a set of images, the image having the largest fractal pixel count selected as the focused image.

Abstract: A method for segmenting an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The image is segmented by thresholding the fractal map of the image.

Abstract: A method for recognizing an object in an image is disclosed wherein a fractal map of the image is generated by estimating the fractal dimension of each pixel in the image. The fractal map is segmented by thresholding and locations of candidate objects are determined. The pixel value of the image pixel corresponding to the same location where the candidate object is found in the fractal map is compared to a threshold value. If the pixel value is greater than the threshold value, the candidate object is recognized as a valid object.

Abstract: A method and system for auto-focusing is disclosed where the number of the fractal pixels having a fractal dimension within a predetermined range is determined. The focused image is determined by adjusting the image to maximize the fractal pixel count. Alternatively, the focused image may be selected from a set of images, the image having the largest fractal pixel count selected as the focused image.

Abstract: A method for classifying objects within a specimen as likely to be premalignant or malignant cells includes the steps of forming an intensity image of a specimen, calculating and storing the maximum and minimum grey scale values at a plural number of distances from a pixel in the intensity image, finding the difference between the maximum and minimum grey scale values at like distances from the pixel, determining the slope of the log of the differences as a function of the log of the distances, storing the slope at the pixel location in a resultant image, and identifying objects in the intensity image as likely to be malignant or premalignant based on the value of the slope.