Abstract:
A diagnostic imaging apparatus and method are provided. The diagnostic imaging apparatus includes a detection unit configured to detect a lesion from a medical image, an interpretation unit configured to acquire a shape feature value by interpreting a shape of the detected lesion in a frequency domain, and a diagnosis unit configured to determine whether the detected lesion is benign or malignant based on the acquired shape feature value.
Abstract:
A method and apparatus for segmenting a contour in an image is provided. The method for segmenting a contour in an image at a processor comprising: creating an initial individual by creating an arbitrary encoding value with respect to an image pixel; creating at least one offspring individual using the initial individual; selecting at least one offspring individual with high fitness from the created offspring individuals; and deriving an individual with highest fitness as a final contour from the selected offspring individuals.
Abstract:
Disclosed is a user interface which enables mark based interaction for images. The present disclosure relates to a user interface which enables mark based interaction for images, the images comprising a volume which is a three-dimensional image and slices which are two-dimensional images, each of which represents a cross section of the volume. At least two of the images each include the same visual mark for identifying at least one common region of interest. The user interface comprises: an input unit for receiving a user input associated with the same visual mark included in one of the images; and at least one component for enabling the interaction for the images including the same visual mark associated with the user input.
Abstract:
An apparatus and method for detecting a lesion, which enables to adaptively determine a parameter value of a lesion detection process using a feature value extracted from a received medical image and a parameter prediction model to improve accuracy in lesion detection and lesion diagnosis. The apparatus and the method include a model generator configured to generate a parameter prediction model based on pre-collected medical images, an extractor configured to extract a feature value from a received medical image, and a determiner configured to determine a parameter value of a lesion detection process using the extracted feature value and the parameter prediction model.
Abstract:
An apparatus and a method for supporting acquisition of a multi-parametric image are provided. An apparatus for supporting acquisition of a multi-parametric image includes: a disease selector configured to select a suspected disease of a patient based on patient information; and an image selector configured to determine a set of imaging conditions of a multi-parametric magnetic resonance image corresponding to the suspected disease based on a multi-parametric magnetic resonance imaging model.
Abstract:
The present disclosure relates to an apparatus for supporting acquisition of an area-of-interest in an ultrasound image. An apparatus for supporting acquisition of an area-of-interest in an ultrasound image according to an aspect of the present disclosure may comprise: at least one processor configured to convert coordinates of one or more areas-of-interest extracted from a first image to coordinates on a 3D model and collect the coordinates on the 3D model of the one or more areas-of-interest; when a second image is acquired, calculate coordinates on the 3D model corresponding to the acquired second image and match the second image onto the 3D model including the coordinates of the collected areas-of-interest; and provide guide information to allow acquisition of the collected areas-of-interest from the second image, using the matching result.
Abstract:
Disclosed are an apparatus and a method for determining lesion similarity of a medical image. The apparatus for determining lesion similarity according to one aspect of the present invention may comprise: an image input unit for receiving a reference image comprising a reference lesion area, and a target image comprising a target lesion area; and a similarity determination unit for determining similarity of the reference lesion area and the target lesion area by applying an advantage weight, which increases as getting closer to the center of the reference lesion area, to pixels included in a first area of the reference lesion area, and a penalty weight, which increases as getting farther away from the reference lesion area, to pixels included in a second area of the target lesion area.
Abstract:
An apparatus and method are provided including a first segmenter and a second segmenter. The first segmenter is configured to generate a first segmentation result from a medical image using a first segmentation parameter for a candidate lesion. The second segmenter is configured to determine a target lesion to segment from among the candidate lesion based on the first segmentation result, and generate a second segmentation result using a second segmentation parameter to segment the target lesion.
Abstract:
A lesion diagnosis apparatus and method for diagnosing images in real time to notify a user that a lesion is detected and providing the user with information about the detected lesion, thereby enhancing accuracy and convenience in a diagnosis. The lesion diagnosis apparatus includes a diagnoser configured to diagnose lesions in images received from a probe; and a guide information provider configured to notify a user that a lesion is detected and to provide guide information, when the lesion is detected.
Abstract:
There are provided an apparatus and a method for acquiring multi-parametric images from an MRI device. In one general aspect, the apparatus for acquiring multi-parametric images includes an image analyzer configured to determine a significance level of each of a plurality of multi-parametric images relating to a disease, and to determine an acquisition order of the multi-parametric images relating to the disease; and a model constructer configured to construct an acquisition model of the multi-parametric images based on the acquisition order and the multi-parametric images to be used in diagnosing the disease.