Lung CT image data segmentation method and system

Abstract

The invention discloses a lung CT image data segmentation method and system, and belongs to the technical field of medical image processing and artificial intelligence. The method comprises the following steps: labeling a lung contour and a target area, and carrying out numerical cutting and normalization processing on image data; performing training learning by using a first neural network to obtain a lung contour segmentation model; extracting a lung contour, determining a lung region of interest, and performing numerical cutting and normalization processing; cutting the lung region of interest, and performing training learning by using a second neural network to obtain a lung target region segmentation model; and segmenting a lung target area according to the image data and the lung target area segmentation model. The system comprises a labeling module, a first cutting normalization module, a first training learning module, a second cutting normalization module, a second training learning module and a detection module. According to the method, the processing efficiency of the lung CT image data is improved, and the target area in the lung CT image data can be quickly segmented.

Description

technical field [0001] The invention relates to the technical fields of medical image processing and artificial intelligence, in particular to a lung CT image data segmentation method and system. Background technique [0002] The image is that CT equipment uses X-ray beams to scan a layer of a certain thickness of a certain part of the human body. The X-rays that pass through this layer are received by the detector and converted into visible light, which is converted from photoelectricity to electrical signals, and then through analog / digital conversion. The converter converts it into a digital signal and inputs it to a computer for processing. CT imaging technology has been widely used in medical examinations, especially the target detection in CT images has become a pre-step for the diagnosis of various diseases. [0003] At present, the target detection in lung CT images is mainly viewed by the doctor's naked eyes. This detection method relies on the doctor's experience ...

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Problems solved by technology

[0004] In order to solve the problems of long time-consuming, slow speed and low efficiency of manual reading of lung CT image data, the present invention provides a lung CT image data segmentation method, including:

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