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Rib fracture AI auxiliary diagnosis method and system based on human chest CT scanning sequence data

A technology of CT scanning and sequence data, applied in image data processing, instruments, calculations, etc., can solve the problem of lack of rib fracture detection system

Pending Publication Date: 2020-10-02
BEIJING PEREDOC TECH CO LTD
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Problems solved by technology

However, there is currently a lack of rib fracture detection systems based on chest CT scan images

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  • Rib fracture AI auxiliary diagnosis method and system based on human chest CT scanning sequence data
  • Rib fracture AI auxiliary diagnosis method and system based on human chest CT scanning sequence data

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Embodiment Construction

[0035] The present invention will be further described below in conjunction with the accompanying drawings. It should be noted that this embodiment is based on the technical solution, and provides detailed implementation and specific operation process, but the protection scope of the present invention is not limited to the present invention. Example.

[0036] figure 1 It is a structural block diagram of a system of an AI-assisted diagnosis method for rib fractures based on human chest CT scan sequence data according to an embodiment of the present invention; figure 2 It is an implementation effect diagram of an AI-assisted diagnosis method and system for rib fractures based on human chest CT scan sequence data according to an embodiment of the present invention, as shown in figure 1 and figure 2 Shown, the present invention comprises the following steps:

[0037] S1. Labeling training and verification of RibsNet, an AI-assisted diagnosis model for rib fractures based on C...

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Abstract

The invention discloses a rib fracture AI auxiliary diagnosis method based on human chest CT scanning sequence data. The rib fracture AI auxiliary diagnosis method comprises the following steps: S1, labeling, training and verifying an AI auxiliary diagnosis model; S2, acquiring CT scanning sequence data; S3, performing pretreatment; S4, carrying out diagnosis: inputting the preprocessed CT image data into an AI auxiliary diagnosis model RibsNet to complete diagnosis, if a suspected focus is detected, outputting prediction data, and otherwise, determining that the prediction data is empty; andS5, outputting diagnosis, carrying out post-processing on the prediction data, then superposing and displaying the prediction data in a chest CT scanning sequence, and displaying fracture suspected focus information. According to the invention, the rib fracture AI auxiliary diagnosis method based on the human chest CT scanning sequence data is adopted; whether the suspected fracture lesion existsin the human chest CT scanning sequence or not can be recognized, meanwhile, the lesion area and the lesion type are accurately identified and displayed, the suspected lesion is scored, a doctor is assisted in screening rib fractures, and the diagnosis efficiency and accuracy are improved.

Description

technical field [0001] The present invention relates to an auxiliary diagnosis technology for rib fractures, in particular to an AI auxiliary diagnosis method and system for rib fractures based on human chest CT scan sequence data. Background technique [0002] Rib fractures and other traumas caused by frequent traffic accidents can cause clinical manifestations such as chest pain, fractures, pneumothorax, and hemothorax, which seriously threaten people's lives. Existing rib fractures are mainly checked by means of CT (computed tomography) imaging scanning. However, due to the constraints of insufficient number of radiologists and heavy workload of film reading, the efficiency of rib fracture screening cannot meet the actual situation. medical needs. [0003] Because the target detection technology in images based on deep learning can input medical imaging data and output AI (artificial intelligence model) assisted diagnosis results, it has the remarkable characteristics of...

Claims

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/0012G06T2207/10081G06T2207/20081G06T2207/20084G06T2207/30008
Inventor 石发强胡飞王方
Owner BEIJING PEREDOC TECH CO LTD
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