Abstract: An apparatus for detecting an error in a contour of a lesion includes an extracting unit configured to extract a contour of a lesion in each of a plurality of two-dimensional image frames that form a three-dimensional image, and an error determining unit configured to determine a presence or an absence of an error in a contour of a lesion in a target image frame of the two-dimensional image frames based on estimation information about the lesion in the target image frame and/or an energy value that corresponds to the contour of the lesion in the target image frame.

Abstract: Provided is a medical imaging apparatus including: an image processor configured to extract properties that an object has with respect to at least one feature, based on a plurality of medical images of the object; and a controller configured to control a display to display a first medical image from among the plurality of medical images and the extracted properties and display a first property shown in the first medical image from among the properties and a second property not shown in the first medical image in such a manner that the first property and the second property are distinguished from each other.

Abstract: An apparatus and method for medical diagnostics includes receiving three-dimensional (3D) volume data of a part of a patient's body, and generating two-dimensional (2D) slices including cross-sections of the 3D volume data cut from a cross-section cutting direction. The apparatus and the method also determine whether a lesion in each of the 2D slices is benign or malignant and output results indicative thereof, select a number of the 2D slices based on the results, and make a final determination whether the lesion is benign or malignant based on the selected 2D slices.

Abstract: An apparatus for detecting a lesion is provided. The apparatus includes an extracting unit configured to extract at least one tissue region from an image of tissue regions, a setting unit configured to set at least one of the at least one extracted tissue region as a lesion detection candidate region, and a detecting unit configured to detect a lesion from the lesion detection candidate region.

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: An apparatus and a method for lesion detection are provided. The method of lesion detection involves detecting lesion candidates from a medical image, detecting anatomical objects from the medical image, verifying each of the lesion candidate based on anatomical context information comprising information regarding a location relationship between the lesion candidates and the anatomical objects, and removing one or more false positive lesion candidate from the detected lesion candidates based on a verification result.

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: An apparatus and a method for diagnosis are provided. The apparatus for diagnosis lesion include: a model generation unit configured to categorize learning data into one or more categories and to generate one or more categorized diagnostic models based on the categorized learning data, a model selection unit configured to select one or more diagnostic model for diagnosing a lesion from the categorized diagnostic models, and a diagnosis unit configured to diagnose the lesion based on image data of the lesion and the selected one or more diagnostic model.

Abstract: An apparatus and method thereof include an observation map generator configured to generate a three-dimensional (3D) observation map based on display frequency and/or display duration of a cross-sectional image of a 3D volume image, wherein the 3D observation map three-dimensionally represents degrees of interest for each voxel of the 3D volume image. The apparatus also includes a region of interest marker configured to mark a region of interest.

Abstract: An apparatus and a method for combining three-dimensional ultrasound images are provide. The method involves obtaining a plurality of three-dimensional ultrasound image data that corresponds to a Region of Interest (ROI); detecting one or more landmarks, using a parameter for detection; outputting the detection result and receiving a response from a user; registering each of one or more selected landmarks as link information according to a received response from the user; and generating a combined three-dimensional ultrasound image by combining at least two pieces of three-dimensional ultrasound image data using at least one of the one or more selected landmarks registered as the link information, wherein the at least two pieces of three-dimensional ultrasound image data commonly comprise the at least one of the one or more selected landmarks.

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: 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 for analyzing a medical image includes an image receiving unit configured to receive two or more medical images from a medical device; a image registration unit configured to register the two or more received medical images; an overlapped area detecting unit configured to detect overlapped areas in the two or more registered medical images; and a lesion analyzing unit configured to analyze lesions in the two or more registered medical images by employing different analysis techniques in the detected overlapped areas.

Abstract: An apparatus for extracting a candidate image frame includes a generating unit configured to generate at least one lesion value that represents a characteristic of a lesion included in each of a plurality of 2-dimensional image frames that form a 3-dimensional image, and an extracting unit configured to extract, from the image frames, at least one candidate image frame usable for correcting a boundary of the lesion based on the at least one lesion value.

Abstract: An apparatus and a method for Computer Aid Diagnosis (CAD) based on eye movement are provided. The apparatus includes a gaze area detector configured to detect, based on eye movement of a user, a gaze area on a medical image on which a region of interest (ROI) is detected, the gaze area being an area at which the user gazes for a period of time. The apparatus further includes an ROI redetector configured to detect another ROI on the gaze area.

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.

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: There is provided an apparatus for visualizing a region of interest (ROI) in a Computer Aided Diagnosis (CAD) system. The apparatus includes: an image receiver configured to receive images; an ROI acquirer configured to acquire the ROI from a current image; and an ROI visualizer configured to, in response to acquisition of the ROI from the current image, output visualization information for visualizing the ROI acquired from the current image based on a change between the ROI acquired from the current image and an ROI acquired from a previous image.

Abstract: A Three-Dimensional (3D) Computer-Aided Diagnosis (CAD) apparatus and method. The 3D CAD apparatus includes: a dimension reducer configured to reduce a dimension of a 3D volume data to generate at least one dimension-reduced image, and a diagnosis component configured to detect a lesion in a 3D volume based on the at least one dimension-reduced image and to diagnose the detected lesion.

Abstract: There is provided an apparatus for supporting Computer Aided Diagnosis (CAD) based on a speed of a probe. The apparatus includes a region of interest (ROI) detector configured to detect an ROI from a current image acquired from a probe; and an ROI classifier configured to determine whether to classify the ROI using a determined state of a speed, and classify the ROI according to a result of the determination.