Abstract: A method and an apparatus for aiding visualization of lesions in a medical image are provided. In detail, the apparatus may receive a user input for selecting a single point in the medical image to modify a lesion mask representing a lesion area in the medical image, may determine a modified lesion mask corresponding to the received user input among a plurality of pre-generated plurality of candidate lesion masks, and may provide the modified lesion mask with the medical image.

Abstract: The present invention relates to a method for classifying a fundus image and a device using same. Specifically, according to the method of the present invention, a computing device acquires a fundus image of a subject, generates classification information of the fundus image, generates an interpretation text on the basis of the classification information, and provides the interpretation text to an external entity.

Abstract: The present invention relates to a method for supporting reading of a fundus image of a subject, and a computing device using the same. Specifically, the computing device according to the present invention acquires the fundus image of the subject, extracts attribute information from the fundus image on the basis of a machine learning model for extracting the attribute information of the fundus image, and provides the extracted attribute information to an external entity. In addition, when evaluation information on the extracted attribute information or modification information on the attribute information is acquired, the computing device according to the present invention can also update the machine learning model on the basis of the acquired evaluation information or modification information.

Abstract: A computing apparatus for aiding visualization of lesions in a medical image includes a communicator and a processor. The processor is configured to receive a user input for selecting a single point in the medical image to modify a lesion mask representing a lesion area in them medical image, determine a modified lesion mask corresponding to the received user input among a plurality of pre-generated plurality of candidate lesion masks, and provide the modified lesion mask with the medical image.

Abstract: The present invention relates to a method for generating a prediction result for predicting an occurrence of fatal symptoms of a subject in advance, a method for performing data classification by using data augmentation in mechanical learning for the same, and a computing device using the same. Particularly, the computing device according to the present invention acquires vital signs of the subject, converts the same into individuated data, generates analysis information from the individuated data on the basis of a machine learning model, generates a prediction result by referring to the analysis information, and provides the prediction result to an external entity.

Abstract: An image providing method performed by a computing apparatus includes acquiring a first image group including at least a portion of a series of images generated for continuous volumes with a first slice thickness belonging to a subject, providing, as a current viewing image, one image of the first image group or one image of a second image group including images generated for continuous volumes with a second slice thickness belonging to the subject, and in response to a first specific input of an input device, repeatedly updating an image provided as the current viewing image with an individual image provided for a subsequent viewing based on a directivity given for the first specific input and, in response to a second specific input of the input device, switching the current viewing image between an image of the first image group and an image of the second image group.

Abstract: Provided are a method for determining whether an examinee is infected by microorganism, and a determination apparatus using the same. Specifically, the determination apparatus according to the present invention obtains an microphotographed image of a biological sample of the examinee; receives the obtained microphotographed image and generates analysis information on the microorganism based on a deep learning model of the examinee; visualize the generated analysis information to provide it, so as to perform at least one of (i) a process of supporting a remote reading on whether the microorganism corresponding to the analysis information exists or not, and (ii) a process of supporting a user of the computing apparatus to read whether the microorganism corresponding to the analysis information exists or not; and provides a final result as its result.

Abstract: According to one embodiment, a method for increasing the reading efficiency of a medical image is provided. The method of increasing the reading efficiency of a medical image comprises of: receiving the gaze information of a user, acquiring a gaze tracking device, during a medical image reading process; determining a region of interest of the user with respect to the medical image by using the gaze information; determining a type of service corresponding to the region of interest; and providing the determined service.

Abstract: A content-based medical image retrieval method and a retrieval system using the same include: obtaining m (2?m?n) number of unit images from a three-dimensional (3D) medical image including n (n?2) number of unit images and extracting features per unit image from each of the m (2?m?n) number of unit images through a feature extraction unit, wherein the 3D medical image is voxel data including a plurality of slices and each of the plurality of slices is defined as a unit image; inputting features of each unit image extracted from the m (2?m?n) number of unit images to a recurrent neural network to generate an output value; and performing medical image retrieval using the output value through an input processing unit, wherein a plurality of 3D medical images to be compared with the output value include a 3D medical image having p (p?2, p?n) number of unit images.

Abstract: According to an embodiment, a method of providing a medical information service is provided. The method for providing a medical information service comprises the steps of: receiving a target image; extracting feature data of the target image; discovering a relative position of the feature data in a disease classification map in which a pre-trained reference image has been quantified; and providing a user with the disease classification map in which the relative position of the feature data has been discovered.

Abstract: Provided are a method and program for computing a bone age using a deep neural network. The method for computing a bone age using a deep neural network, including: receiving an analysis target image that is a specific medical image to compute the bone age; and analyzing the analysis target image by at least one computer using the deep neural network to compute the bone age. According to the present disclosure, since the bone age is computed by accumulating medical images of a specific race (particularly, Korean) and analyzing the same, it is possible to compute an accurate bone age that conforms to race.