Abstract: According to the present disclosure, provided are a method for harmonizing a medical image which includes receiving a medical image for an object, and harmonizing the received medical image to acquire a filtered medical image by using a convolutional filter based on a predictive model trained to output a reconstructed image using the medical image as input, in which the convolutional filter corresponds to a first convolutional layer of the predictive model, and a device using the same and the present disclosure is a technology developed through the Seoul Business Agency of the Seoul Metropolitan Government (2023 Bio-Medical Technology Commercialization Support Project BT230080 Validation of Safety and Efficacy of Echocardiographic Imaging Diagnosis Solution through Myocardial Texture Analysis Based on Ultrasound Imaging).

Abstract: The present invention provides a method for providing information on an M-mode ultrasound image implemented by a processor and device using same, the method comprising the steps of: receiving an M-mode ultrasound image of a subject; segmenting a plurality of cardiac tomographic regions within the M-mode ultrasound image by using a segmentation model that is trained so as to segment the M-mode ultrasound image into a plurality of cardiac tomographic regions; and determining measurements for the plurality of segmented cardiac tomographic regions.

Abstract: The present invention provides a method for providing information regarding an ultrasound image view, which is implemented by a processor, and a device using the method, the method comprising the steps of: receiving an ultrasound image of an object; and classifying respective image views on the basis of the received ultrasound image, by using an image view classification model trained to classify a plurality of image views by using an ultrasound image as an input and output respective image views, wherein the respective image views indicate ultrasound image views in a plurality of different ultrasound modes.

Abstract: Abstract as amended below shows added text with underlining and deleted text with The present disclosure provides a method, implemented by a processor, for providing information about a doppler ultrasound image, and a device using the same, the method including receiving a first image showing a portion of an individual's heart and a second image showing the flow or velocity of blood; and classifying a view of the second image on the basis of the received first and second images by using a view classification model trained to classify a view by using each of the first and second images as inputs.

Abstract: Provided according to an embodiment of the present invention are a method and an apparatus for providing uncertainty data for a predicted target region in a medical image. Also provided according to an embodiment of the present invention are a method and an apparatus for screening a medical image for labeling.

Abstract: The present invention provides a method for providing information on an M-mode ultrasound image implemented by a processor and device using same, the method comprising the steps of: receiving an M-mode ultrasound image of a subject; segmenting a plurality of cardiac tomographic regions within the M-mode ultrasound image by using a segmentation model that is trained so as to segment the M-mode ultrasound image into a plurality of cardiac tomographic regions; and determining measurements for the plurality of segmented cardiac tomographic regions.

Abstract: The present invention provides an echocardiography guide method implemented by means of a processor, and a device using same, the echocardiography guide method comprising the steps of: receiving an echocardiographic image of an individual; segmenting a cross section of the echocardiographic image into a plurality of cardiac monolayer regions; calculating, on the basis of a standard cross section received in advance, a matching rate for the cross section from which the plurality of cardiac monolayer regions is segmented; determining, on the basis of the matching rate of the cross section, whether to provide a guide; and, in response to whether to provide the guide, providing the guide for acquiring a cross section having a preset matching rate or higher.

Abstract: According to the present disclosure, provided are a method for harmonizing a medical image which includes receiving a medical image for an object, and harmonizing the received medical image to acquire a filtered medical image by using a convolutional filter based on a predictive model trained to output a reconstructed image using the medical image as input, in which the convolutional filter corresponds to a first convolutional layer of the predictive model, and a device using the same and the present disclosure is a technology developed through the Seoul Business Agency of the Seoul Metropolitan Government (2023 Bio-Medical Technology Commercialization Support Project BT230080 Validation of Safety and Efficacy of Echocardiographic Imaging Diagnosis Solution through Myocardial Texture Analysis Based on Ultrasound Imaging).

Abstract: In order to determine presence or absence of abnormality in an internal organ or muscle, a method of determining presence or absence of abnormality in an internal organ or muscle may include obtaining at least one image of the internal organ or muscle, determining at least one feature matrix for the at least one image, determining a feature value for measuring a tissue phenotype from the at least one feature matrix, and determining presence or absence of the abnormality in the internal organ or muscle using a trained artificial intelligence model. The feature value may include items selected as information indicating the tissue phenotype of the internal organ or muscle, and the items may be selected using a machine learning model among candidate feature values determinable from the at least one feature matrix.

Abstract: In order to detect medical indices in a medical image, a method of obtaining information from a medical image may include performing segmentation on regions of a heart in the medical image, generating at least one reference line based on the segmentation and determining at least one medical index based on the at least one reference line.

Abstract: In order to detect medical indices in a medical image, a method of obtaining information from a medical image may include performing segmentation on regions of a heart in the medical image, generating at least one reference line based on the segmentation and determining at least one medical index based on the at least one reference line.

Abstract: The present invention relates to predicting a future onset possibility of a disease by using an artificial intelligence algorithm, and a method for predicting the onset of the disease may include: obtaining input data based on medical checkup data of a subject; generating output data indicating an onset possibility of the disease by year from the input data by using a trained artificial intelligence model; determining at least one item with a relatively high contribution to a result of the output data; and outputting information regarding the onset possibility of the disease by year and the at least one item.