Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
An SVD-based grayscale image quality measure for local and global assessment
IEEE Transactions on Image Processing
A human inspired local ratio-based algorithm for edge detection in fluorescent cell images
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Predicting segmentation accuracy for biological cell images
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
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We have developed a method to rapidly test the quality of a biological image, to identify appropriate segmentation methods that will render high quality segmentations for cells within that image. The key contribution is the development of a measure of the clarity of an individual biological cell within an image that can be quickly and directly used to select a segmentation method during a high content screening process. This method is based on the gradient of the pixel intensity field at cell edges and on the distribution of pixel intensities just inside cell edges. We have developed a technique to synthesize biological cell images with varying qualities to create standardized images for testing segmentation methods. Differences in quality indices reflect observed differences in resulting masks of the same cell imaged under a variety of conditions.