Abstract:
An apparatus and method for adapting a diagnostic model for Computer-Aided Diagnosis (CAD). The CAD apparatus includes an image acquirer configured to acquire an image of an object, a diagnosis model store configured to store at least one diagnostic model, an adaptive information provider configured to provide adaptive information regarding the image, a diagnostic model adapter configured to select a diagnostic model from the diagnostic model store and to generate an adapted diagnostic model based on the selected diagnostic model and the adaptive information, and a diagnoser configured to perform CAD on the image using the adapted diagnostic model.
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:
There is provided an image segmentation apparatus and related method for enhancing accuracy of image segmentation based on user interaction. The image segmentation apparatus including an interface configured to, in response to an image displayed on the interface, receive information about the image from a user and a segmenter configured to segment the contour of a region of interest (ROI) in the image based on the information.
Abstract:
Provided are apparatuses and methods for analyzing a lesion in an image. A Threshold Adjacency Statistics (TAS) feature may be extracted from a medical image, and a pattern of the lesion may be classified using the extracted TAS feature.
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:
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 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:
A diagnosis aiding apparatus and method to provide diagnosis information is provided. The diagnosis aiding apparatus includes an information display unit configured to display a reference cross-section of an image, display diagnosis information belonging to the reference cross-section, and display diagnosis information corresponding to a different cross-section within the reference cross-section displayed.
Abstract:
A lesion diagnosis apparatus and a lesion diagnosis method are provided. A lesion-surrounding area determination unit is configured to determine an existence of a lesion-surrounding area from continuous medical images. A feedback provision unit is configured to generate feedback information about a presence of a lesion in the lesion-surrounding area.
Abstract:
A computer-aided diagnosis (CAD) method includes extracting a lesion feature value of a lesion feature of a lesion from a captured lesion image; receiving additional information; and diagnosing the lesion based on a combination of the extracted lesion feature value and the received additional information.