Samsung Electronics Co., Ltd.

Seoul National University

Samsung Life and Welfare Foundation

Ye-hoon Kim

Yeong-Kyeong Seong

Baek-Hwan Cho

Moon-ho Park

Jung-Hoe Kim

Ki-Yong Lee

Min Woo Lee

Jin-Ho Lee

Jun-ik Jang

So-jung Yun

Sin-Sang Yu

Jin-ho Lee

Do-Jun Yang

Kyoung-Gu Woo

Han-sung Lee

Seok-Jin Hong

Keun-joo Kwon

Soon-hyuk Hong

Joo-Hyuk Jeon

Myung-Eun Lee

Jong-Hyo Kim

Hyeong-Min Jin

Jun-Ik Jang

Han-Sung Lee

Soon-Hyuk Hong

An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Apparatus and method for processing image

An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

Electronic apparatus for determining a dangerous situation of a vehicle and method of operating the same

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.

User interface system and method for enabling mark-based interaction for images

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.

Contour segmentation apparatus and method based on user interaction

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.

Apparatus and method for computer-aided diagnosis

A method of displaying electrocardiograms comprises displaying a reference electrocardiogram; and displaying a measured electrocardiogram so that the reference electrocardiogram and the measured electrocardiogram are displayed in an overlapping state.

Method and user interface device for displaying electrocardiograms

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.

Apparatus and method for lesion segmentation and detection in medical images

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.

Apparatus and method for combining three dimensional ultrasound images

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.

Apparatus and method for detecting lesion

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Seoul, South Korea

Ye-hoon Kim