Abstract: Disclosed is a method for analyzing a lesion based on a medical image performed by a computing device. The method may includes generating, by using a pre-processing module, an input image of a pre-trained detection module from the medical image. The method may include generating, by using the detection module, a probability value regarding a presence of a nodule in at least one region of interest and first location information about the at least one region of interest, based on the input image. The method may include determining, by using a post-processing module, second location information about a suspicious nodule present in the medical image from the first location information, based on the probability value regarding the presence of the nodule.

Abstract: The present disclosure relates to a method of aiding visualization of lesions in a medical image and an apparatus using the same. In detail, according to the method of the present disclosure, a lesion visualization aiding method 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: 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: Disclosed is a method for analyzing a lesion based on a medical image, which is performed by a computing device. The method may include: obtaining positional information of a suspicious nodule which exists in the medical image; generating a mask for the suspicious nodule based on a patch of the medical image corresponding to the positional information; and determining a class for a state of the suspicious nodule based on the patch of the medical image and the mask for the suspicious nodule.

Abstract: An embodiment of the present disclosure provides a method of providing a User Interface for serial images analysis in a user equipment, the method including: displaying a first cross-sectional image, a second cross-sectional image, and a third cross-sectional image on a first area of the user interface, which are related to a first image; displaying candidate nodule information related to the first image on at least one of the first cross-sectional image, the second cross-sectional image, and the third cross-sectional image; determining the candidate nodule information related to a user input as first nodule information related to the first image, based on the user input on the user interface; and displaying the first nodule information in such a way that the candidate nodule information related to the user input is replaced with the first nodule information, in which the candidate nodule information may be generated based on a first nodule dataset obtained by inputting the first image to a deep learning algo

Abstract: The present disclosure relates to a method of aiding visualization of lesions in a medical image and an apparatus using the same. In detail, according to the method of the present disclosure, a lesion visualization aiding method 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.