Medical image lung nodule detection method based on anti-network

A technology for medical images and detection methods, applied in the field of image processing, can solve the problems of inability to detect lung nodules and insufficient utilization, and achieve the effect of improving robustness and detection accuracy

Inactive Publication Date: 2018-06-15
XIDIAN UNIV
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Problems solved by technology

However, because this method still uses the traditional method to recommend candidate nodules, it fails to make full use of the advantages o...

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  • Medical image lung nodule detection method based on anti-network
  • Medical image lung nodule detection method based on anti-network
  • Medical image lung nodule detection method based on anti-network

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Embodiment Construction

[0021] Refer to the following figure 1 , to further describe the specific embodiments and effects of the present invention.

[0022] Step 1, acquire medical images.

[0023] Randomly select images of 100 cases from the original data set of the Lung Image Database Consortium LIDC, extract the coordinate information of lung nodules by reading the XML format annotation file of the original data set, and use the case images and lung nodule coordinate information to form samples data set.

[0024] Step 2, introduce Gaussian noise to expand the data sample set.

[0025] Data augmentation is performed on the data sample set, that is, the data sample is scaled and cut, and all samples are copied, and Gaussian noise is added to the copied data sample to form an expanded sample data set. The specific implementation is as follows:

[0026] (2a) By adaptively cropping images containing lung nodules: Locate the nodule center in the image containing lung nodules, use it as the cropping c...

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Abstract

The invention discloses a medical image lung nodule detection method based on an anti-network, which mainly solves the problem of low detection precision due to shading on medical image lung nodules in the prior art. The method comprises the steps of: 1) preprocessing a medical image to acquire a sample data set; 2) scaling and cutting the sample data set, and adding Gaussian noise to all processed samples to form an expanded sample data set; 3) superimposing a Faster-RCNN detector with an anti-space discarding network (ASDN) to construct a novel detector based on the anti-network; 4) trainingthe novel detector with the sample data set to obtain a trained novel detection model; and 5) performing lung nodule detection on a test data set with the trained detection model to obtain a lung nodule detection result in each medical image. The method improves the detection precision of medical image lung nodules and can be used in a computer aided diagnosis system.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a method for detecting pulmonary nodules in medical images, which can be used in a computer-aided diagnosis system. Background technique [0002] Pulmonary nodules are one of the most important early signs of lung cancer. According to the lesion characteristics of pulmonary nodules, the lesion characteristics of lung lesions can be inferred. Therefore, early detection and treatment of pulmonary nodules in patients with lung diseases is a key measure to reduce lung cancer mortality. Due to its high morbidity and mortality, lung cancer has become the deadliest tumor among cancers. With the change of people's living habits and the deterioration of the environment, the number of people with lung cancer is increasing, and the society is paying more and more attention to it. Combined with the medical characteristics of pulmonary nodules, using deep learning technology to proc...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/73G06K9/62
CPCG06T7/0012G06T7/75G06T2207/20084G06T2207/20081G06T2207/20104G06T2207/30064G06F18/214
Inventor 姬红兵王厚华张文博朱志刚王益新
Owner XIDIAN UNIV
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