Abstract: Techniques for processing images to be used for more accurate measurement of biological processes such as cell migration, as well as techniques for measuring cell migration. A method for processing microscopic images includes generating a smoothed image for a raw image by applying a smoothing filter to the raw image, wherein the raw image shows a plurality of cells and a background; generating a high pass filter image by dividing the raw image by the smoothed image; and transforming the high pass filter image into a transformed image by augmenting the spatial frequency of the plurality of cells shown in the high pass filter image with respect to the background.

Abstract: A method and system for image-based region detection. Transformation matrices are computed by performing image registration between a target image and each of one or more reference images. Each transformation matrix is for transforming each of the reference images into a coordinate system of the target image. An optimal reference image is selected from among the reference images based on similarity measures between the target image and each reference image. The transformation matrix of the selected reference image is applied to a reference map associated with the reference image in order to generate a target map for the target image. The target map includes region labels indicating regions shown in the target image.

Abstract: Techniques for processing images to be used for more accurate measurement of biological processes such as cell migration, as well as techniques for measuring cell migration. A method for processing microscopic images includes generating a smoothed image for a raw image by applying a smoothing filter to the raw image, wherein the raw image shows a plurality of cells and a background; generating a high pass filter image by dividing the raw image by the smoothed image; and transforming the high pass filter image into a transformed image by augmenting the spatial frequency of the plurality of cells shown in the high pass filter image with respect to the background.

Abstract: A method and system for preprocessing microscopic images. A method includes identifying a plurality of microglial cells shown in microglial cell channel images, wherein identifying the plurality of microglial cells further comprises quantizing the microglial cell channel microscopic images and filtering a plurality of objects in the quantized microglial cell channel microscopic images; identifying a soma and at least one projection for each of the plurality of microglial cells, wherein identifying the soma and the at least one projection for each microglial cell further includes iteratively removing pixels on the microglial cell as shown in one of the microglial cell channel images, wherein each soma and each projection has a respective size; and determining an activation state of each microglial cell based on the size of the soma and a total size of the at least one projection identified for the microglial cell.

Abstract: A system and method for microscopic image processing. The method includes cleaning leaks shown in images to create cleaned images, each of the images having a neuron signal intensity, wherein the images include at least one neuron channel image and at least one oligodendrocyte channel image, wherein cleaning the images further includes applying a filtering function to each of the images and adjusting the neuron signal intensity of each of the images based on an output of the filtering function; detecting oligodendrocytes in the cleaned images, wherein each detected oligodendrocyte is a region of the images including an object for which the neuron signal intensity is within a range of neuron signal intensities; and identifying high-intensity sub-regions within each detected oligodendrocyte, wherein each high-intensity sub-region includes at least one high-intensity object, wherein each high-intensity object is an object for which the neuron signal intensity is above a threshold.

Abstract: A method and system for image-based region detection. Transformation matrices are computed by performing image registration between a target image and each of one or more reference images. Each transformation matrix is for transforming each of the reference images into a coordinate system of the target image. An optimal reference image is selected from among the reference images based on similarity measures between the target image and each reference image. The transformation matrix of the selected reference image is applied to a reference map associated with the reference image in order to generate a target map for the target image. The target map includes region labels indicating regions shown in the target image.

Abstract: A method and system for preprocessing microscopic images. A method includes identifying a plurality of microglial cells shown in microglial cell channel images, wherein identifying the plurality of microglial cells further comprises quantizing the microglial cell channel microscopic images and filtering a plurality of objects in the quantized microglial cell channel microscopic images; identifying a soma and at least one projection for each of the plurality of microglial cells, wherein identifying the soma and the at least one projection for each microglial cell further includes iteratively removing pixels on the microglial cell as shown in one of the microglial cell channel images, wherein each soma and each projection has a respective size; and determining an activation state of each microglial cell based on the size of the soma and a total size of the at least one projection identified for the microglial cell.

Abstract: A system and method for microscopic image processing. The method includes cleaning leaks shown in images to create cleaned images, each of the images having a neuron signal intensity, wherein the images include at least one neuron channel image and at least one oligodendrocyte channel image, wherein cleaning the images further includes applying a filtering function to each of the images and adjusting the neuron signal intensity of each of the images based on an output of the filtering function; detecting oligodendrocytes in the cleaned images, wherein each detected oligodendrocyte is a region of the images including an object for which the neuron signal intensity is within a range of neuron signal intensities; and identifying high-intensity sub-regions within each detected oligodendrocyte, wherein each high-intensity sub-region includes at least one high-intensity object, wherein each high-intensity object is an object for which the neuron signal intensity is above a threshold.