Focus lung segment position identification method and device, storage medium and electronic equipment

Abstract

The invention relates to a focus lung segment position identification method and device, a storage medium and electronic equipment. The focus lung segment position identification efficiency and the focus lung segment position identification result reliability are improved. The method comprises the following steps: acquiring a target lung image marked with a focus position; the target lung image is input into a lesion lung segment position recognition model, a lung segment position recognition result corresponding to the lesion in the target lung image is obtained, and the lung segment position recognition result is used for representing the lung segment position of the lesion in the lung; wherein the focus lung segment position identification model comprises a first classification sub-model and a second classification sub-model, the first classification sub-model is used for classifying a target lung image according to a lung segment category corresponding to the target lung image, and inputting the classified target lung image into the second classification sub-model corresponding to the lung segment category, the second classification sub-model is used for determining a lung segment position identification result corresponding to the focus in the target lung image.

Description

technical field [0001] The present disclosure relates to the technical field of image processing, and in particular, to a method, device, storage medium and electronic equipment for identifying the position of a lung segment of a lesion. Background technique [0002] CT (Computed Tomography), that is, electronic computer tomography, it uses X-ray beams to scan a layer of a certain thickness of the human body. The X-rays that pass through this layer are received by the detector and converted into visible light. It is an electrical signal, which is then converted into a digital signal by an analog / digital converter and input to a computer for processing. As the most effective non-invasive detection technology for lung diseases, lung CT images are widely used in lung disease screening and auxiliary diagnosis due to its advantages of thin layers, high definition, and low noise. [0003] At present, lung CT image analysis technology mainly studies whether there are lesions in th...

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Problems solved by technology

[0004] The purpose of this disclosure is to provide a method, device, storage medium and electronic equipment for identifying the position of the lung segment of th

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