Abstract: The disclosed technology relates to a method and device for generating a fat suppression magnetic resonance image. The method includes: inputting, by an imaging device, a magnetic resonance image to an encoder of a neural network to extract features of the magnetic resonance image; and generating, by a generator of the neural network, a T2-weighted fat suppression image based on the features, in which the neural network is trained according to a result of discriminating, by a discriminator of the neural network, a loss due to a generation of a T2-weighted fat suppression image and as a result of reconstructing, by a decoder, the magnetic resonance image input to the encoder using a Bloch equation before the magnetic resonance image is input.

Abstract: Disclosed is a method of predicting a prognosis of a patient with adenocarcinoma using image features. The method of predicting a prognosis according to an embodiment of the present invention includes receiving an image including a lesion region of a patient, preprocessing the received image, segmenting the lesion region in the preprocessed image and calculating at least one of biomarkers indicating an intensity value and a texture information value within the segmented lesion region, and outputting a prognosis prediction value of the patient on the basis of the calculated at least one biomarker.

Abstract: A makeup evaluation system can include a mobile terminal for photographing an image and transmitting the photographed image to a makeup server; and a makeup server including a make-up DB management unit for storing at least one algorithm used for make-up evaluation, a region detection unit for detecting a face region in the photographed image, a makeup analysis unit for evaluating makeup by applying the stored algorithm to the detected face region, and a wireless communication unit for transmitting an evaluation result signal including information on the result of evaluating the makeup to the mobile terminal, in which the mobile terminal displays the evaluation result according to a received evaluation result signal, and the makeup server evaluates makeup by applying different algorithms for each face region.

Abstract: The disclosed technology relates to a method and device for generating a fat suppression magnetic resonance image. The method includes: inputting, by an imaging device, a magnetic resonance image to an encoder of a neural network to extract features of the magnetic resonance image; and generating, by a generator of the neural network, a T2-weighted fat suppression image based on the features, in which the neural network is trained according to a result of discriminating, by a discriminator of the neural network, a loss due to a generation of a T2-weighted fat suppression image and as a result of reconstructing, by a decoder, the magnetic resonance image input to the encoder using a Bloch equation before the magnetic resonance image is input.

Abstract: A makeup evaluation system can include a mobile terminal for photographing an image and transmitting the photographed image to a makeup server; and a makeup server including a make-up DB management unit for storing at least one algorithm used for make-up evaluation, a region detection unit for detecting a face region in the photographed image, a makeup analysis unit for evaluating makeup by applying the stored algorithm to the detected face region, and a wireless communication unit for transmitting an evaluation result signal including information on the result of evaluating the makeup to the mobile terminal, in which the mobile terminal displays the evaluation result according to a received evaluation result signal, and the makeup server evaluates makeup by applying different algorithms for each face region.

Abstract: A makeup evaluation system according to an embodiment of the present invention includes a mobile terminal for photographing a facial image and transmitting the photographed facial image to a makeup server, and the makeup server for storing makeup score data and, when receiving the facial image from the mobile terminal, detecting at least one face region in the facial image, calculating a makeup score for each of the detected face regions on the basis of the makeup score data, and transmitting the calculated makeup score to the mobile terminal.

Abstract: A neural waveform distinguishment apparatus includes: a neural waveform obtainment unit that obtains multiple neural waveforms in a pre-designated manner from neural signals sensed by way of at least one electrode; a preprocessing unit that obtains multiple gradient waveforms by calculating pointwise slopes in each of the neural waveforms; a feature extraction unit comprising an encoder ensemble composed of multiple encoders, which have a pattern estimation method learned beforehand and include different numbers of hidden layers, where the feature extraction unit obtains multiple codes as multiple features extracted by the encoders respectively from the gradient waveforms and concatenates the codes extracted by the encoders respectively to extract a feature ensemble for each of the gradient waveforms; and a clustering unit that distinguishes the neural waveforms corresponding respectively to the gradient waveforms by clustering the feature ensembles extracted respectively in correspondence to the gradient wav

Abstract: A makeup evaluation system according to an embodiment of the present invention includes a mobile terminal for photographing a facial image and transmitting the photographed facial image to a makeup server, and the makeup server for storing makeup score data and, when receiving the facial image from the mobile terminal, detecting at least one face region in the facial image, calculating a makeup score for each of the detected face regions on the basis of the makeup score data, and transmitting the calculated makeup score to the mobile terminal.

Abstract: Provided are a method and apparatus for processing a magnetic resonance (MR) image of an object including first and second materials on a magnetic resonance imaging (MRI) apparatus by using multi-parameter mapping including applying to the object a plurality of radio frequency (RF) pulses separated by a first repetition time and a second repetition time, the first repetition time and the second repetition time being determined based on the first material and the second material; undersampling first MR signals corresponding to the first material and second MR signals corresponding to the second material in a K-space; and performing matching between the undersampled first and the undersampled second MR signals and a signal model for the multi-parameter mapping to determine attribute values corresponding to the first and the second materials at at least one point in an MR image of the object.

Abstract: A method and an apparatus for adjusting the parameters of a magnetic resonance image are disclosed. An embodiment of the invention provides a method for adjusting a parameter at an imaging device that includes: (a) obtaining and storing MR (magnetic resonance) data; (b) calculating a constant by using the MR data; and (c) outputting a magnetic resonance image having a different contrast in real time, when a user manipulation is inputted, by using the constant and a parameter adjusted according to the manipulation.

Abstract: Provided is a magnetic resonance imaging (MRI) apparatus.

Abstract: Provided is a magnetic resonance imaging (MRI) apparatus. The MRI apparatus includes: a data acquisition unit configured to acquire a first k-space including a first missing line by undersampling an MR signal received from an object at a first time point, acquire a second k-space including a first acquired line corresponding to the first missing line by undersampling an MR signal received from the object at a second time point, and acquire a third k-space including a second acquired line corresponding to the first missing line by undersampling an MR signal received from the object at a third time point; and an image processor configured to interpolate data in the first missing line based on data in the first and second acquired lines.

Abstract: A denoising method and apparatus for multi-contrast MRI's are disclosed. An aspect of the invention provides a denoising method for an MRI that includes: acquiring multiple MRI's having different contrast levels for the same site; determining pixels corresponding to the same tissue by using the MRI's; and calculating a new luminance value for the pixels by using luminance values of the pixels that are determined to be belonging to the same tissue.

Abstract: A method and apparatus for envelope detection are disclosed. An envelope detection method according to an embodiment of the invention can include: receiving ultrasonic signals reflected off a target object; detecting peaks by using differences in pulses in the received signals; and generating an envelope by connecting the detected peaks with straight or curved lines.

Abstract: Provided are a method and apparatus for processing a magnetic resonance (MR) image of an object including first and second materials on a magnetic resonance imaging (MRI) apparatus by using multi-parameter mapping including applying to the object a plurality of radio frequency (RF) pulses separated by a first repetition time and a second repetition time, the first repetition time and the second repetition time being determined based on the first material and the second material; undersampling first MR signals corresponding to the first material and second MR signals corresponding to the second material in a K-space; and performing matching between the undersampled first and the undersampled second MR signals and a signal model for the multi-parameter mapping to determine attribute values corresponding to the first and the second materials at at least one point in an MR image of the object.

Abstract: Disclosed are an apparatus and a method for removing noise from biosignals. An embodiment of the invention provides an apparatus for removing noise from biosignals measured for a particular period of time that includes: a similarity calculating unit configured to calculate a similarity between any one biosignal from among the biosignals and other biosignals; and a noise removal unit configured to remove noise from the any one biosignal by using the similarity. Aspects of the invention provide the advantage of effectively removing noise from biosignals without distorting the waveforms of the biosignals.

Abstract: A method and an apparatus for adjusting the parameters of a magnetic resonance image are disclosed. An embodiment of the invention provides a method for adjusting a parameter at an imaging device that includes: (a) obtaining and storing MR (magnetic resonance) data; (b) calculating a constant by using the MR data; and (c) outputting a magnetic resonance image having a different contrast in real time, when a user manipulation is inputted, by using the constant and a parameter adjusted according to the manipulation.

Abstract: A method of controlling of an R-peak detection apparatus, which detects an R-peak from an ElectroCardioGram (ECG) signal, includes receiving the ECG signal, reading out a pre-stored ECG template, comparing the EG signal with the pre-stored ECG template to determine a similarity between the ECG signal and the pre-stored ECG template and determining whether the similarity is equal to or greater than a threshold value, and determining a corresponding interval as the R-peak when the similarity is equal to or greater than the threshold value.

Abstract: Provided is a magnetic resonance imaging (MRI) apparatus. The MRI apparatus includes: a data acquisition unit configured to acquire a first k-space including a first missing line by undersampling an MR signal received from an object at a first time point, acquire a second k-space including a first acquired line corresponding to the first missing line by undersampling an MR signal received from the object at a second time point, and acquire a third k-space including a second acquired line corresponding to the first missing line by undersampling an MR signal received from the object at a third time point; and an image processor configured to interpolate data in the first missing line based on data in the first and second acquired lines.

Abstract: A denoising method and apparatus for multi-contrast MRI's are disclosed. An aspect of the invention provides a denoising method for an MRI that includes: acquiring multiple MRI's having different contrast levels for the same site; determining pixels corresponding to the same tissue by using the MRI's; and calculating a new luminance value for the pixels by using luminance values of the pixels that are determined to be belonging to the same tissue.