Abstract:
A method of reconstructing a tomography image and a tomography apparatus configured to reconstruct a tomography image are provided. Tomography data corresponding to a moving object is acquired by performing a tomography scan on the object, and a tomography image is reconstructed using prior images obtained based on the acquired tomography data.
Abstract:
An image processing apparatus is provided. The image processing apparatus includes a processor configured to, in response to an image including a plurality of frames being input, change a predetermined parameter to a parameter corresponding to a compression rate of each of the plurality of frames for each frame, and process the input image by using the parameter changed for each frame, and an output interface configured to output the processed image.
Abstract:
An image processing apparatus is disclosed. The image processing apparatus of the present invention comprises: an image receiving unit for receiving a first image and a second image of the same object taken at different times; a processor for obtaining transformation information by registering the first image on the basis of the second image, obtaining a first segment image corresponding to an area of the object from the first image, and generating a second segment image corresponding to an area of the object of the second image by transforming the obtained first segment image according to the transformation information; and an output unit for outputting the second segment image.
Abstract:
The present invention relates to an image processing apparatus, an image processing method, and a recording medium for recording the same, the image processing apparatus including a storage configured to comprise a standard database (DB) established based on information about a predetermined anatomical entity; and at least one processor configured to obtain a local motion vector by registration between a first medical image and a second medical image taken by scanning an object including the anatomical entity, use a predictive local motion vector generated from the standard DB to normalize the local motion vector according to a plurality of regions in the anatomical entity, and make information about conditions of the anatomical entity based on the normalized local motion vector be provided according to the plurality of regions. By the normalization according to the regions, it is possible to provide distinguishable information about difference between the local motion vector of a pulmonary disease patient to be subjected to a diagnosis and a predictive local motion vector of a normal person generated from the standard DB through the statistical modeling using bio-information of a patient.
Abstract:
Disclosed are a medical image display device for displaying a screen including a medical image and a medical image processing method thereof, the medical image display device comprising: a display configured to display a first medical image obtained by photographing an object comprising at least one anatomical entity; and at least one processor configured to extract reference region information corresponding to the anatomical entity from at least one second medical image used as a reference image for the first medical image, detect a region corresponding to the anatomical entity from the first medical image based on the extracted reference region information, and control the display to display the region of the detected anatomical entity to be distinguishable from at least one region unrelated to the anatomical entity.
Abstract:
A super-resolution processing method of a moving image is provided. The super-resolution processing method of a moving image includes sequentially inputting a plurality of input frames included in the video to any one of a recurrent neural network (RNN) for super-resolution processing and a convolutional neural network (CNN) for super-resolution processing, sequentially inputting a frame sequentially output from the any one of the RNN and the CNN to an additional one of the RNN and the CNN, and upscaling a resolution of the output frame by carrying out deconvolution with respect to a frame sequentially output from the additional one of the RNN and the CNN.
Abstract:
A method of processing a medical image includes acquiring a three-dimensional (3D) medical image indicating a blood vessel and a two-dimensional (2D) medical image indicating the blood vessel, determining a blood vessel area in the 3D medical image corresponding to a partial area of the blood vessel in the 2D medical image, and matching the blood vessel area with the partial area in the 2D medical image.
Abstract:
Disclosed are a method and an apparatus, which enhance a quality of an ultrasound image to provide an improved image. An adaptive demodulation method includes acquiring input radio frequency (RF) data, quadrature-demodulating the input RF data to output an inphase-quadrature (IQ) signal, determining a valid region for the input RF data, and estimating attenuation of a frequency of the IQ signal, based on data included in the valid region among the input RF data and performing frequency compensation corresponding to the estimated attenuation of the frequency.
Abstract:
A medical imaging apparatus includes a data acquirer configured to acquire measured data acquired by detecting an X-ray transmitted by an X-ray source to an object, and an image processor configured to acquire an initial image based on the measured data, alternately estimate region of interest (ROI)-outside measured data and ROI-inside measured data based on the measured data and the initial image, and acquire a reconstructed image based on the ROI-inside measured data.
Abstract:
Disclosed is an image processing apparatus. The present image processing apparatus comprises: an input unit for inputting an image; and a processor for shrinking the inputted image to a predetermined ratio, extracting a visual feature from the shrunken image, performing an image quality enhancement process reflecting the extracted visual feature in the inputted image, repeatedly performing, for a predetermined number of times, the shrinking, the extracting, and the image quality enhancement process on the image that has undergone the image quality enhancement process. The present disclosure relates to an artificial intelligence (AI) system and an application thereof that simulate the functions of a human brain, such as recognition, judgment, etc., by using a machine learning algorithm such as deep learning, etc.