Lg Display Co., Ltd.

Infinitt Healthcare Co., Ltd.

Lg Innotek Co., Ltd.

Han Young Kim

Hyun Ho Choi

Sang Hun Lee

Young Seop Moon

Hyung Ki Kim

Ui Jun Kim

Dae Kyu Yi

Sang Wook Cho

Wonhoon Choi

Disclosed herein are a system and method for assisting the verification of the contouring of medical images. A system for assisting the verification of the contouring of medical images according to an embodiment of the present invention receives a medical image set including a plurality of medical images via the communication interface, receives the result information of contouring performed on a plurality of regions of interest (ROIs) on the plurality of medical images in the medical image set via the communication interface, calculates the feature value of each of the plurality of ROIs, corresponding to the result information of the contouring, for each of the plurality of medical images, and displays the boundary of each of the plurality of ROIs corresponding to the result information of the contouring by projecting the boundary onto a reference plane.

System and method for assisting verification of labeling and contouring of multiple regions of interest

Disclosed herein are a system and method for contouring a set of medical images. The system for contouring a set of medical images receives a medical image set including a plurality of medical images via the communication interface module, receives region-of-interest (ROI) information as an object for the drawing of a contour via the user interface module, checks whether a contour corresponding to the ROI information has been drawn on a target image currently displayed to a user, predicts a contour candidate based on contouring conditions if the contour corresponding to the ROI information has not been drawn on the target image, and displays the contour candidate on the target image. The contouring conditions include the relevance between at least one source image, on which the contour corresponding to the ROI information has been already drawn, and the target image, and anatomical information related to the ROI information.

System and method for contouring a set of medical images based on deep learning algorithm and anatomical properties

The present embodiment relates to a dual camera module comprising: a first camera module including a first liquid lens and capturing a first image; and a second camera module including a second liquid lens and capturing a second image, wherein a viewing angle of the first camera module is smaller than a viewing angle of the second camera module, at least a part of the viewing angle of the first camera module is included in the viewing angle of the second camera module such that there is an overlapping area between the first image and the second image so as to enable a composite image formed by combining the first image and the second image to be generated, and when the first camera module is focused, a focal length of the first liquid lens is varied according to the distance between the first liquid lens and a subject, and when the second camera module is focused, a focal length of the second liquid lens is varied according to the distance between the second liquid lens and the subject.

Dual camera module, optical device, camera module, and method for operating camera module

Disclosed are a computing system and method for identifying and visualizing a thrombosis. The method includes: registering an acquired computer tomography (CT) image of an examinee and a computer tomography angiography (CTA) image-based average standard model to each other; identifying a candidate blood vessel region from the CT image based on the results of the registration; acquiring a volume, selected by applying a threshold value for the brightness of the CT image to the candidate blood vessel region, as a first thrombosis candidate region; acquiring at least part of the first thrombosis candidate region as a second thrombosis candidate region based on the size information of the first thrombosis candidate region; and visualizing the second thrombosis candidate region by assigning a visual effect, adapted to distinguish the second thrombosis candidate region from the remaining portion of the CT image, to the second thrombosis candidate region.

Computing system and method for identifying and visualizing cerebral thrombosis based on medical images

Provided is a display device. The display device comprises a receiving unit, a liquid crystal panel, and a backlight assembly. The receiving unit comprises a sidewall, a first support bent or curved to extend from the sidewall, a second support bent or curved to extend from the first support. The second support faces the sidewall. At least one of the liquid crystal panel and the backlight assembly is received in the receiving unit. The liquid crystal panel and the backlight assembly can be doubly protected by the sidewall and the second support, and a display device with improved mechanical strength can be realized.

Display device

A display device according to an embodiment includes a liquid crystal panel; a backlight assembly disposed below the liquid crystal panel; a chassis including: a first support section, which is disposed at sides of the liquid crystal panel and the backlight assembly, and a second support section, which is bent or curved from the first support section; and a frame disposed at an inner side of the chassis, wherein the frame has a first frame, a second frame, a third frame and a fourth frame and at least one of the first to the fourth frames has a height lower than a height of the first support section.

Disclosed is a display device. The display device comprises a liquid crystal panel, a backlight assembly disposed below the liquid crystal panel, a frame receiving at least a part of the liquid crystal panel and the backlight assembly, and a chassis disposed at the frame. At least a part of the chassis is inserted into the frame, so that the strength of the frame and the chassis can be improved.

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Seoul, South Korea

Han Young Kim