A method for estimating an onset time of acute cerebral infarction, the method comprising: receiving, by a computer, a first image and a second image of a specific first patient whose acute cerebral infarction onset time is not identified, the first image is a fluid-attenuated inversion recovery image, and the second image is a diffusion-weighted image; extracting, by the computer, an infarction region image from the second image; aligning, by the computer, the second image with the first image to define an infarction region in the first image, based on a result of the alignment of the second image with the first image; comparing the infarction region with a symmetric region located in a brain of the first patient and being symmetrical to the infarction region to extract a relative signal amount of the infarction region, based on a result of the comparison of the infarction region with the symmetric region; generating a ratio map that includes a relative signal amount between the symmetric region and the infarction region, extracting, by the computer, feature information of the first patient, from the infarction region in the first image by applying at least one of Gray Level Cooccurrence Matrix (GLCM), Run-Length Matrix (especially, Gray Level Run-Length Matrix (GLRLM)), and Local Binary Pattern, to the signal intensity and gradient of the infarction region; comparing, by the computer, the extracted feature information with reference data to calculate an amount of time that has elapsed since the acute cerebral infarction onset time, based on a result of the comparison of the extracted feature information with the reference data; wherein the feature information includes first feature information extracted from the infarction region in the first image; and second feature information extracted from an infarction region in the ratio map for the first image, and wherein the extracting of the infarction region image from the second image comprises: normalizing an intensity of an apparent diffusion coefficient map of the second image; and extracting the infarction region image via an absolute reference value search in the normalized apparent diffusion coefficient map. receiving, by a computer, a first image and a second image of a specific first patient whose acute cerebral infarction onset time is not identified, the first image is a fluid-attenuated inversion recovery image, and the second image is a diffusion-weighted image; extracting, by the computer, an infarction region image from the second image; aligning, by the computer, the second image with the first image to define an infarction region in the first image, based on a result of the alignment of the second image with the first image; comparing the infarction region with a symmetric region located in a brain of the first patient and being symmetrical to the infarction region to extract a relative signal amount of the infarction region, based on a result of the comparison of the infarction region with the symmetric region; generating a ratio map that includes a relative signal amount between the symmetric region and the infarction region, extracting, by the computer, feature information of the first patient, from the infarction region in the first image by applying at least one of Gray Level Cooccurrence Matrix (GLCM), Run-Length Matrix (especially, Gray Level Run-Length Matrix (GLRLM)), and Local Binary Pattern, to the signal intensity and gradient of the infarction region; comparing, by the computer, the extracted feature information with reference data to calculate an amount of time that has elapsed since the acute cerebral infarction onset time, based on a result of the comparison of the extracted feature information with the reference data; wherein the feature information includes first feature information extracted from the infarction region in the first image; and second feature information extracted from an infarction region in the ratio map for the first image, and wherein the extracting of the infarction region image from the second image comprises: normalizing an intensity of an apparent diffusion coefficient map of the second image; and extracting the infarction region image via an absolute reference value search in the normalized apparent diffusion coefficient map. first feature information extracted from the infarction region in the first image; and second feature information extracted from an infarction region in the ratio map for the first image, and wherein the extracting of the infarction region image from the second image comprises: normalizing an intensity of an apparent diffusion coefficient map of the second image; and extracting the infarction region image via an absolute reference value search in the normalized apparent diffusion coefficient map. normalizing an intensity of an apparent diffusion coefficient map of the second image; and extracting the infarction region image via an absolute reference value search in the normalized apparent diffusion coefficient map.