Pulmonary nodule automatic detection method and device and computer system

Abstract

The invention relates to a pulmonary nodule automatic detection method, a pulmonary nodule automatic detection device and a computer system. The method comprises the following steps: acquiring a CT image to be detected; performing filtering enhancement processing on the CT image to be detected to obtain a lung enhanced CT image sequence; segmenting the CT image sequence by adopting a threshold method to obtain an image only containing a pulmonary parenchyma region; cutting the image obtained by the pulmonary parenchyma segmentation module into a plurality of image blocks, and obtaining a region of interest through a multi-scale feature fusion UNet network model; and carrying out automatic detection and identification on the region of interest by adopting a 3D CNN model to obtain a pulmonary nodule detection result. Compared with the prior art, the method has the advantages of high detection sensitivity and precision and the like.

Description

technical field

[0001] The invention relates to the field of computer aided detection, in particular to an automatic detection method, device and computer system for pulmonary nodules. Background technique

[0002] Lung cancer is one of the tumor diseases with the highest mortality rate. Every year, more than 1.3 million people die from lung cancer in the world. In the early stage of lung cancer, its performance is not obvious, and more than 70% of lung cancer patients are basically in the advanced stage of lung cancer. According to relevant medical statistics, if lung cancer patients can get proper intervention treatment in the early stage of cancer, their 5-year survival rate can reach more than 90%, but the survival rate of lung cancer patients in stage 2-3 drops to 40%-5%. Therefore, "early detection, early diagnosis, and early treatment" is the key to improving the survival rate of lung cancer patients. Lung cancer usually manifests as pulmonary nodules in the early ...

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