Heuron Co., Ltd.

Gachon University of Industry-academic Cooperation Foundation

Gil Medical Center

Soohwa Song

Dohyun Kim

Jin Soo Lee

Seong Joon Lee

Sumin Jung

Jisu Hong

Hanyong Chun

Ji Woo Song

Donghyuk Lee

Gyu Ha Park

Seontae Kim

Seung Yon Koh

A large vessel occlusion (LVO) test device using eyeball deviation includes an image input unit configured to input non-contrast computed tomography (CT); a pre-processing unit; an image processing unit; and a determination unit. The objects include both eyes and the upper part of the brain corresponding to the entire cerebral cortex from the midbrain. The image processing unit configured to non-rigid register at least one atlas for the non-cis contrast CT images pre-processed from the pre-processing unit, normalize each cell of the non-contrast CT image to which the atlas is registered to have a value of 0 or 1, and extract a region of interest in a restored non-contrast CT image by combining each cell of the non-contrast CT image to which the atlas is registered through inverse transformation.

Large vessel occlusion test device and method using eyeball deviation

An aspect of the present disclosure provides an apparatus for extracting a vascular function including an information reception unit configured to extract an original CT image from brain-related information received from the outside; an NIFTI image transformation unit configured to transform the original CT image into an NIFTI file format image to acquire time sequence data; a time interpolation unit configured to apply time interpolation to the original CT image through the time sequence data to transform the original CT image into each time-specific 3D CT image; a vessel segmentation unit configured to predict a vessel segmentation mask by passing the each time-specific 3D CT image through a deep learning-based vessel segmentation deep-learning modeland generate a 4D vessel mask image by stacking the 3D CT images based on a time axis; and a vascular function extraction unit configured to extract a vascular function from a vessel region of the 4D vessel mask image and calculate a blood flow parameter using an artery function which is one of the vascular functions.

Apparatus and method for extracting vascular function from brain-related information

The present disclosure relates to artificial intelligence-based devices and methods for geometric alignment and preprocessing of raw CT images. According to the present disclosure, when sensitive to a local error according to each characteristic, only linear transformation is applied to use the centrally aligned rigid registration result, and when the region of interest between patients is spatially matched or monitoring is required, a non-rigid registration result may be used.

Artificial intelligence-based devices and methods for geometric alignment and preprocessing of raw CT images

The present disclosure relates to a method, an apparatus, and a system for detecting and classifying an ischemic stroke based on a medical image. A medical image based ischemic stroke detecting and type classifying apparatus according to an aspect of the present disclosure includes an acquiring unit which collects images related to a brain of at least one patient; a detecting unit which determines whether the at least one patient is a large vessel occlusion patient, based on the collected image; a determining unit which determines whether a type of the large vessel occlusion is embolism or intracranial atherosclerosis (ICAS), when the at least one patient is a large vessel occlusion patient; and a diagnosing unit which provides treatment direction information which is applied differently according to the determined type of the large vessel occlusion.

Ischemic stroke detection and classification method based on medical image, apparatus and system

A device and a method for detecting a tumor using a medical image and diagnosing a shape and a property of the detected tumor are disclosed. An exemplary medical image-based tumor detection and diagnostic device includes: an input unit configured to obtain a medical image related to a patient; a preprocessing unit configured to preprocess the obtained medical image to observe a tumor region; an analysis unit configured to divide the preprocessed image into a plurality of regions by applying a deep neural network-based deep learning technique; and a measurement unit configured to group the plurality of divided regions by performing clustering on the plurality of divided regions. The measurement unit extracts a group feature value in respect to each of the grouped regions and derives diagnosis information related to the tumor based on the extracted group feature value.

Medical image-based tumor detection and diagnostic device

Disclosed is a sinus balloon catheter. The sinus balloon catheter includes a body unit, a bending angle adjusting unit that includes a bending angle adjusting lever and a rotary plate, and a guide unit that includes a balloon, and has a pair of bending angle adjusting wires therein. The guide unit includes a first guide body, and a second guide body that is slidably provided in the first guide body, the balloon is provided on the second guide body, the rotary plate is connected to any one of the pair of bending angle adjusting wires to be rotated, and the other bending angle adjusting wire is maintained within the guide unit, and the guide unit is inserted into any one of a sphenoidal sinus, a frontal sinus, and a maxillary sinus.

Growing community of inventors

Incheon, South Korea

Soohwa Song