Abstract: A method for training a medical image performed by a medical image processing apparatus for processing a medical image for a body is provided. The method for training a medical image includes preparing a first input data set including a training chest X-ray image, and a bone enhancement image or a bone extraction image acquired from the training chest X-ray image; preparing a label data for the first input data set including osteoporosis information or bone mineral density information corresponding to the training chest X-ray image; and training an artificial neural network model using the first input data set and the label data.

Abstract: A method for training a medical image performed by a medical image processing apparatus for processing a medical image for a body is provided. The method for training a medical image includes preparing a first input data set including a training chest X-ray image, and a bone enhancement image or a bone extraction image acquired from the training chest X-ray image; preparing a label data for the first input data set including osteoporosis information or bone mineral density information corresponding to the training chest X-ray image; and training an artificial neural network model using the first input data set and the label data.

Abstract: A system for diagnosing osteoporosis according to an embodiment includes a classification model training device that includes a plurality of classification models, one or more of the plurality of classification models being artificial intelligence models corresponding to each of a plurality of segmented images which are obtained by segmenting an entire image corresponding to each anatomical area, and trains a corresponding classification model based on the plurality of segmented images and training labels corresponding to each segmented image, the training label being labeled as normal or the osteoporosis, and a bone disease classification device that diagnoses whether there is the osteoporosis by inputting the plurality of segmented images segmented from a read target image to the corresponding classification model of the classification model training device.

Abstract: A method for training a medical image performed by a medical image processing apparatus for processing a medical image for a body is provided. The method for training a medical image includes preparing a first input data set including a training chest X-ray image, and a bone enhancement image or a bone extraction image acquired from the training chest X-ray image; preparing a label data for the first input data set including osteoporosis information or bone mineral density information corresponding to the training chest X-ray image; and training an artificial neural network model using the first input data set and the label data.

Abstract: A method for training a medical image performed by a medical image processing apparatus for processing a medical image for a body is provided. The method for training a medical image includes preparing a first input data set including a training chest X-ray image, and a bone enhancement image or a bone extraction image acquired from the training chest X-ray image; preparing a label data for the first input data set including osteoporosis information or bone mineral density information corresponding to the training chest X-ray image; and training an artificial neural network model using the first input data set and the label data.