Acer Inc.

Far Eastern Memorial Hospital

Ai-Hsien Li

Cheng-Tien Hsieh

Yun-Huan Lyu

Wen-Po Chuang

A blood vessel detecting apparatus and an image-based blood vessel detecting method are provided. In the method, first to-be-evaluated data is detected through a first detecting model to obtain a first detection result. Second to-be-evaluated data is detected through a second detecting model to obtain a second detection result. The first to-be-evaluated data includes one or more medical images obtained from photographing a blood vessel. The first detection result output by the first detecting model includes one or more pixels in the medical image belonging to the blood vessel. The first detecting model and the second detecting model are constructed based on a machine learning algorithm. The second to-be-evaluated data includes the first detection result. The second detection result output by the second detecting model includes one or more pixels in the medical image belonging to the blood vessel.

Blood vessel detecting apparatus and image-based blood vessel detecting method

A blood vessel status evaluation method and a blood vessel status evaluation device are provided. The method includes: obtaining at least one angiography image corresponding to a target user; analyzing the angiography image by a first deep learning model to select a target image from the angiography image; analyzing the target image by at least one second deep learning model to determine a blood vessel type of the target user and divide a target blood vessel pattern in the target image into a plurality of scoring segments; and analyzing an output of the second deep learning model by a third deep learning model to obtain a blood vessel status of the target user.

Blood vessel status evaluation method and blood vessel status evaluation device

A blood vessel status evaluation method and a blood vessel status evaluation device are provided. The method includes: obtaining at least one angiography image corresponding to a target user; selecting a target image from the angiography image; determining a blood vessel type of the target user according to a distribution status of a target blood vessel pattern in the target image; establishing a blood vessel topology structure corresponding to the target blood vessel pattern which includes information of a width of a blood vessel in the target blood vessel pattern and information of an intersection of blood vessel in the target blood vessel pattern; and automatically analyzing a blood vessel status of the target user according to the blood vessel type and the blood vessel topology structure.

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Taipei, Taiwan

Ai-Hsien Li