The method of estimating the ASPECT score according to the present invention includes a preprocessing step of normalizing and standardizing features of an image dataset by a preprocessor； A segmentation step of the image processing unit separating each lesion within the CT image classified into a supra ganglion level and a ganglion level； And a determining step of determining whether the lesion has a stroke by independently building a neural network for learning a positive/negative image for each lesion by the determination unit； including, wherein the pre-processing step includes convolution of Gaussian blur on the entire patient's brain CT image A noise removal step of removing noise included in the image； A search step of searching for a skull ellipse to find a skull in the brain CT image； An alignment step of aligning the position of the image based on the searched center point of the skull and rotating the image to uniformly align the position and rotation angle of the dataset； And performing a horizontal transformation according to the lesion location (Lesion-Side)； wherein the searching step includes searching for an adaptive threshold value in consideration of the distribution of pixel values of the segmented image, and An automatic thresholding step of inducing only the pixel information corresponding to to remain； A contour search step of detecting an edge based on the image for which the thresholding has been completed； And acquiring skull ellipse information for acquiring information on the inner and outer edges of the skull by searching for the skull ellipse from the image remaining only the edge information.본 발명에 따른 ASPECT 스코어를 추정하는 방법은, 전처리부가 영상 데이터세트의 특징을 정규화하고 표준화하는 전처리 단계； 영상처리부가 수프라 신경절 레벨과 신경절 레벨로 분류된 CT 영상 내에서 각 병변을 분리하는 분할 단계； 및 판단부가 각 병변 별로 양성/음성 영상을 학습하는 신경망을 독립적으로 구축하여 병변의 뇌졸중 여부를 판단하는 판단 단계；를 포함하되, 상기 전처리 단계는, 환자의 뇌 CT 영상 전체에 가우시안 블러를 컨볼루션해서 영상에 포함된 노이즈를 제거하는 노이즈 제거 단계； 상기 뇌 CT 영상에서 두개골을 찾기 위해 두개골 타원을 검색하는 검색 단계； 검색된 두개골의 중심점을 기준으로 영상의 위치를
