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 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 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 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: 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 interpolating a lesion area when diagnosis is performed in a Computer Aided Diagnosis (CAD) system using consecutive images. According to an example, the apparatus includes: an image receiver configured to receive images sequentially; an image matcher configured to match a current image with reference images, and to determine whether to interpolate a lesion area in the current image based on a matching result; and a lesion area acquirer configured to interpolate or acquire the lesion area in the current image according to a result of the determination.

Abstract: An apparatus and method for adaptive computer-aided diagnosis (CAD) are provided. The adaptive CAD apparatus includes an image analysis algorithm selector configured to select an image analysis algorithm based on a speed of a probe or a resolution of a current image frame obtained by the probe; and an image analyzer configured to detect and classify a region of interest (ROI) in the current image frame using the selected image analysis algorithm.

Abstract: Technology related to an apparatus and method for supporting a diagnosis of a lesion is provided. The apparatus includes a standard image determiner to determine, as a standard image, an image where a region of interest (ROI) is detected among a plurality of images received from an image collecting device, a candidate image extractor to extract one or more candidate images with respect to the determined standard image, a comparison image selector to select one or more comparison images for supporting a diagnosis of the ROI from the one or more candidate images, and an interface to provide a user with an output result of the standard image and the one or more selected comparison images.

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: A method of visualizing anatomical elements in a medical includes receiving a medical image; detecting a plurality of anatomical elements from the medical image; verifying a location of each of the plurality of anatomical elements based on anatomical context information including location relationships between the plurality of anatomical elements; adjusting the location relationships between the plurality of anatomical elements; and combining the verified and adjusted information of the plurality of anatomical elements with the medical image.

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: A method and an apparatus for modifying a contour line of an object are provided. The method involves displaying a contour line of an object on a screen, receiving a plurality of touch points, matching each of the plurality of the received touch points with corresponding contour line points on the contour line, generating touch point movement data by tracing a movement path of each of the plurality of the received touch points, determining a curvature variation of the contour line based on the touch point movement data, and modifying the contour line by moving each of the corresponding contour line points based on the touch point movement data and applying the curvature variation to a section connected between each of the moved corresponding contour line points to generate the section.

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: 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 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 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 includes an interface unit configured to provide, to a terminal, an interface supporting one or more modes, and display, on the interface, an image including a contour of a region of interest. The apparatus further includes a contour modification unit configured to modify the contour based on a mode selected by a user from the one or more modes, and an operation performed by the user.

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: A method and apparatus to analyze received measured medical data and display correlated analysis results are provided. A method of displaying an analysis result of measured data, includes analyzing measured data received for disease diagnosis and deriving results of analysis items based on the analyzed measured data. The method further includes displaying the results by setting each of the analysis items as a variant and allowing correlated ones of the analysis items to be disposed adjacent to each other.