Deep-learning-based early screen apparatus for lung cancer

Abstract

The invention provides a deep-learning-based early screen apparatus for the lung cancer. The apparatus is composed of an image processing module, an image analysis module, an image analysis result processing module. The image processing module is used for preprocessing an image to obtain an image meeting a deep learning standard. The image analysis module is used for inputting the image into a neural network after deep learning to detect a lung nodule in the image, so that the neural network outputs a suspicious lung nodule and a corresponding confidence value. The image analysis result processing module is used for selecting N highest values, extracting a last convolution layer for each highest value, introducing extraction results into a pooling layer and an all-connection layer, and thus calculating the probability of the lung cancer. According to the deep-learning-based early screen apparatus provided by the invention, the blank of the intelligent device for early screening of thelung cancer is filled and an automatic low-cost high-confidence apparatus is provided for intelligent medical imaging diagnosis. The operation has characteristics of full automation and manual intervention prevention, so that the precious time of the medical staff is saved; and the lung cancer prediction rate is consistent.

Description

technical field [0001] The invention relates to the field of medical equipment, in particular to a device for early screening of lung cancer based on deep learning. Background technique [0002] Lung cancer is one of the cancers with the highest mortality rate worldwide. Lung cancer was reported to have caused 1.6 million deaths in 2012, and 1.8 million cases were diagnosed as lung cancer. Early lung cancer screening plays a key role in the diagnosis and treatment of lung cancer. According to investigations, low-dose CT screening can reduce lung cancer mortality by 20%. [0003] Traditional lung cancer screening relies on professional medical personnel to interpret lung LDCT images to screen out suspicious lung nodules. Nodules in the lungs are strongly associated with lung cancer. This traditional method is extremely demanding on the workload of medical personnel and is prone to false positive diagnoses. Thereby increasing additional medical expenses and increasing the...

AI Technical Summary

Problems solved by technology

The traditional CAD system has certain limitations in the detection and diagnosis of pulmonary nodules

Images