CN113903452B - Auxiliary diagnosis system for pulmonary nodules of doctors - Google Patents

Auxiliary diagnosis system for pulmonary nodules of doctors Download PDF

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CN113903452B
CN113903452B CN202111096725.1A CN202111096725A CN113903452B CN 113903452 B CN113903452 B CN 113903452B CN 202111096725 A CN202111096725 A CN 202111096725A CN 113903452 B CN113903452 B CN 113903452B
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周成伟
金炜
邬贤巧
房天政
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Affiliated Hospital of Medical School of Ningbo University
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Abstract

The invention belongs to the technical field of medical diagnosis, and discloses a doctor pulmonary nodule auxiliary diagnosis system which is provided with a main body device, a pulmonary nodule auxiliary diagnosis prompt device, an input device and a display device, wherein the input device is used for inputting basic information and clinic information of a patient and a pulmonary nodule image of the patient; the pulmonary nodule auxiliary diagnosis prompting device is arranged inside the main body device and comprises an information image memory for storing basic information and clinic information of the patient input by the input device and a pulmonary nodule image of the patient; an image processing module, a lung nodule identification module and a communication module are arranged in the main body device; the image processing module comprises. According to the invention, the image processing module, the lung nodule identification module and the communication module are arranged in the main body device, and the communication module is connected with the cloud server, so that the big data processing, judging and analyzing can be realized, and the diagnosis accuracy and efficiency are improved.

Description

Auxiliary diagnosis system for pulmonary nodules of doctors
Technical Field
The invention belongs to the technical field of medical diagnosis, and particularly relates to a pulmonary nodule auxiliary diagnosis system for doctors.
Background
At present, lung cancer is one of the cancers with higher incidence in the world today. About 120 million people are diagnosed with lung cancer each year, and about 110 million people die of lung cancer. If lung cancer patients are diagnosed in early stage, the five-year survival rate can reach more than 70%, however, lung cancer patients are mostly in middle and late stages when being diagnosed, and the operation time is lost. If diagnosed early, five-year survival rates can exceed 70%. If the early diagnosis of the lung cancer can be carried out and corresponding measures are taken, the early diagnosis has important significance for improving the survival time and the life quality of patients. At present, pathological diagnosis is the gold standard for determining lung cancer, but the diagnosis is traumatic, and the application in clinic is limited. In recent years, for the diagnosis of lung cancer, digitization is more clear and convenient, and the like, and thus, the method has become a mainstream image inspection method for the diagnosis of lung cancer. In medical image diagnosis, conventional image features such as color, texture, shape, and the like are generally described. Texture is an important feature in an image and can provide important information for identifying and interpreting the image. Due to the wide variety and diversity of texture forms, texture has not been a formal definition of which is widely accepted. It is generally considered that the texture features of an image describe the change of the gray level or color of the surface of an object, and the change is related to the property of the object itself and is the repetition of some texture elements. In the processing of medical images containing nodules, it is important to identify the nature of the nodules in the images. However, the existing lung nodule diagnosis mainly depends on the experience of a radiologist, and no system capable of effectively assisting the radiologist to perform lung nodule diagnosis exists, so that the accuracy and efficiency of diagnosis are reduced.
Through the above analysis, the problems and defects of the prior art are as follows: the existing lung nodule diagnosis mainly depends on the experience of a radiologist, and no system capable of effectively assisting the radiologist to diagnose the lung nodule exists, so that the accuracy and efficiency of diagnosis are reduced.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a system for assisting diagnosis of a pulmonary nodule of a doctor.
The invention is realized in such a way that a doctor lung nodule auxiliary diagnosis system is provided with a main body device, a lung nodule auxiliary diagnosis prompting device, an input device and a display device, wherein the input device is used for inputting basic information and clinic information of a patient and a lung nodule image of the patient;
the pulmonary nodule auxiliary diagnosis prompting device is arranged inside the main body device and comprises an information image memory for storing basic information and clinic information of the patient input by the input device and a pulmonary nodule image of the patient;
an image processing module, a lung nodule identification module and a communication module are arranged in the main body device; the image processing module includes: the system comprises an image preprocessing module and an image depth processing and identifying module;
the image depth processing and identifying module is provided with an image segmentation module, an image feature extraction module and an image feature matching module;
the image preprocessing module is used for preprocessing the lung nodule image input by the input device for inputting the basic information and the clinic information of the patient and the lung nodule image of the patient;
after the image preprocessing is finished, a lung nodule identification module identifies a lung nodule image;
in the image identification process, extracting the lung nodule image characteristics through an image characteristic extraction module; acquiring a pulmonary nodule image prestored in a cloud server through a communication module;
performing similarity calculation matching on the acquired image and the lung nodule image through an image feature matching module, and determining the lung nodule when the similarity is within a certain range;
the specific process of determining the similarity between the acquired image and the lung nodule image by the image feature matching module is as follows:
determining and extracting a key point descriptor subset from the acquired image and the lung nodule image,
the lung nodule image keypoints are described as: r i ＝(r i1 ，r i2 ，…，r i128 )；
The key points of the acquired image are described as follows: s. the i ＝(s i1 ，s i2 ，…，s i128 )；
The similarity measurement between the lung nodule image key point and the acquired image key point is as follows:
Figure BDA0003269287700000031
the numerical range for determining the similarity of the lung nodules is:
Figure BDA0003269287700000032
further, the memory driver connected with the information image memory and the texture arithmetic unit connected with the information image memory are connected; an information image memory, a memory driver and an extraction controller connected to the texture operator.
Further, the specific process of the lung nodule image key points and the obtained image key points description is as follows:
converting the corresponding image into a Gaussian image, and determining an image area for describing the key point by solving the gradient;
rotating the coordinate axis as the direction of the key point, and determining the invariance of rotation; and distributing sampling points inside the field to corresponding sub-regions;
determining the gradients of each seed in eight directions by utilizing interpolation, and limiting the gradient amplitude value of the direction histogram in each direction below a threshold value;
after the feature vector is formed, the descriptor vector is normalized.
Further, the image pre-processing module comprises:
the image graying processing module is used for carrying out weighted average on the RGB three components according to the importance and the index to obtain a more reasonable grayscale image;
the image geometric transformation processing module is used for processing the acquired image through translation, transposition, mirroring, rotation and geometric transformation of zooming and is used for correcting the system error and the instrument position of the image acquisition system;
and the image enhancement processing module is used for regarding the image as a two-dimensional signal through a frequency domain method and enhancing the signal based on two-dimensional Fourier transform.
Further, the display device is an LCD panel, and the display device is disposed on the main body device.
Further, the input device comprises a keyboard and a mouse.
Further, the main body device is also provided with an interface for connecting a printer.
Further, the main body device is in a rectangular parallelepiped or square shape.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the physician lung nodule auxiliary diagnosis system when executed on an electronic device.
It is another object of the present invention to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to execute the system for assisting diagnosis of pulmonary nodules by a physician.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the invention, the image processing module, the lung nodule identification module and the communication module are arranged in the main body device, and the communication module is connected with the cloud server, so that the big data processing, judging and analyzing can be realized, and the diagnosis accuracy and efficiency are improved. By arranging the pulmonary nodule auxiliary diagnosis prompting device, the invention can prompt diagnosis in time, improves the intellectualization and avoids the diagnosis error. Meanwhile, the invention inputs the basic information and the information of the patient and the lung nodule image of the patient through the input device, can acquire comprehensive data, is convenient for the later diagnosis and analysis and can accurately obtain the diagnosis result.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a system for assisting diagnosis of a pulmonary nodule provided by a doctor according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a connection relationship structure of an information image storage according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a main device according to an embodiment of the present invention.
Fig. 4 is a flowchart of a method for processing an image by a main apparatus according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for describing key points of a lung nodule image and key points of an acquired image according to an embodiment of the present invention.
In the figure: 1. a main body device; 2. a pulmonary nodule auxiliary diagnosis prompting device; 3. an input device; 4. a display device.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
In view of the problems in the prior art, the present invention provides a system for assisting diagnosis of pulmonary nodules by a doctor, and the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a system for assisting diagnosis of a pulmonary nodule provided by a doctor in an embodiment of the present invention includes: the system comprises a main body device 1, a lung nodule auxiliary diagnosis prompting device 2, an input device 3 for inputting basic information and clinic information of a patient and a lung nodule image of the patient, and a display device 4;
the lung nodule auxiliary diagnosis prompting device 2 is arranged inside the main body device and comprises an information image memory for storing basic information and clinic information of the patient input by the input device and a lung nodule image of the patient.
Wherein, the display device 1 is an LCD panel, and the display device is arranged on the main body device; the input device 3 comprises a keyboard and a mouse; the main body device 1 also has an interface for connecting a printer, and the main body device 1 is in the shape of a rectangular parallelepiped or a cube.
As shown in fig. 2, the connection relationship of the information image memory provided by the embodiment of the present invention is:
the memory driver is connected with the information image memory, and the texture arithmetic unit is connected with the information image memory; an information image memory, a memory driver and an extraction controller connected to the texture operator.
As shown in fig. 3, the main apparatus 1 provided in the embodiment of the present invention is further internally provided with an image processing module, a lung nodule recognition module and a communication module; the image processing module includes: the system comprises an image preprocessing module and an image depth processing and identifying module; the image depth processing and identifying module is provided with an image segmentation module, an image feature extraction module and an image feature matching module.
As shown in fig. 4, the specific process of processing an image by the main apparatus 1 according to the embodiment of the present invention is as follows:
s101: the image preprocessing module preprocesses the lung nodule image input by the input device for inputting the basic information and the doctor seeing information of the patient and the lung nodule image of the patient;
s102: after the image preprocessing is finished, a lung nodule identification module identifies a lung nodule image;
s103: in the image identification process, extracting the lung nodule image characteristics through an image characteristic extraction module; acquiring a lung nodule image prestored in a cloud server through a communication module;
s104: and performing similarity calculation matching on the acquired image and the lung nodule image through an image feature matching module, and determining the lung nodule when the similarity is within a certain range.
The specific process of determining the similarity between the acquired image and the lung nodule image by the image feature matching module provided by the embodiment of the invention is as follows:
determining and extracting a key point descriptor set in the acquired image and the lung nodule image,
the lung nodule image keypoints are described as: r is i ＝(r i1 ，r i2 ，…，r i128 )；
The key points of the acquired image are described as follows: s i ＝(si 1 ，si 2 ，…，s i128 )；
The similarity measure of the lung nodule image key points and the acquired image key points is as follows:
Figure BDA0003269287700000061
the numerical range for determining the similarity of the lung nodules is:
Figure BDA0003269287700000062
as shown in fig. 5, the specific process of describing the lung nodule image key points and the acquired image key points provided by the embodiment of the present invention is as follows:
s201: converting the corresponding image into a Gaussian image, and determining an image area for describing the key point through solving the gradient;
s202: rotating the coordinate axis as the direction of the key point, and determining the invariance of the rotation; and distributing sampling points inside the field to corresponding sub-regions;
s203: determining the gradients of each seed in eight directions by utilizing interpolation, and limiting the gradient amplitude value of the direction histogram in each direction below a threshold value;
s204: after the feature vector is formed, the descriptor vector is normalized.
The image preprocessing module provided by the embodiment of the invention comprises:
the image graying processing module is used for carrying out weighted average on the RGB three components according to the importance and the index to obtain a more reasonable grayscale image;
the image geometric transformation processing module is used for processing the acquired image through translation, transposition, mirroring, rotation and geometric transformation of zooming and is used for correcting the system error and the instrument position of the image acquisition system;
and the image enhancement processing module is used for regarding the image as a two-dimensional signal through a frequency domain method and enhancing the signal based on two-dimensional Fourier transform.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.

Claims (6)

1. A doctor pulmonary nodule auxiliary diagnosis system is characterized by being provided with a main body device, a pulmonary nodule auxiliary diagnosis prompting device, an input device and a display device, wherein the input device is used for inputting basic information and diagnosis information of a patient and a pulmonary nodule image of the patient;
the pulmonary nodule auxiliary diagnosis prompting device is arranged inside the main body device and comprises an information image memory for storing basic information and clinic information of the patient input by the input device and a pulmonary nodule image of the patient;
an image processing module, a lung nodule identification module and a communication module are arranged in the main body device; the image processing module includes:
the image preprocessing module and the image depth processing and identifying module;
the image depth processing and identifying module is provided with an image segmentation module, an image feature extraction module and an image feature matching module;
the image preprocessing module preprocesses the lung nodule image input by the input device for inputting the basic information and the doctor seeing information of the patient and the lung nodule image of the patient;
after the image preprocessing is finished, a lung nodule identification module identifies a lung nodule image;
in the image identification process, extracting the lung nodule image characteristics through an image characteristic extraction module; acquiring a lung nodule image prestored in a cloud server through a communication module;
performing similarity calculation matching on the acquired image and the lung nodule image through an image feature matching module, and determining the lung nodule when the similarity is within a certain range;
the specific process of determining the similarity between the acquired image and the lung nodule image by the image feature matching module is as follows:
determining and extracting a key point descriptor set in the acquired image and the lung nodule image,
the lung nodule image keypoints are described as: r i ＝(r i1 ，r i2 ，…，r i128 )；
The key points of the acquired image are described as follows: s. the i ＝(s i1 ，s i2 ，…，s i128 )；
The similarity measurement between the lung nodule image key point and the acquired image key point is as follows:
Figure FDA0003898013510000011
the numerical range for determining the similarity of the lung nodules is:
Figure FDA0003898013510000021
the memory driver is connected with the information image memory, and the texture arithmetic unit is connected with the information image memory; the information image memory, the memory driver and the extraction controller are connected with the texture arithmetic unit;
the specific process of the description of the lung nodule image key points and the acquired image key points is as follows:
converting the corresponding image into a Gaussian image, and determining an image area for describing the key point through solving the gradient;
rotating the coordinate axis as the direction of the key point, and determining the invariance of rotation; and distributing sampling points inside the field to corresponding sub-regions;
determining the gradients of each seed in eight directions by utilizing interpolation, and limiting the gradient amplitude value of the direction histogram in each direction below a threshold value;
after the feature vector is formed, normalizing the descriptor vector;
the image preprocessing module comprises:
the image graying processing module is used for carrying out weighted average on the RGB three components according to the importance and the index to obtain a more reasonable grayscale image;
the image geometric transformation processing module is used for processing the acquired image through translation, transposition, mirroring, rotation and geometric transformation of zooming and is used for correcting the system error and the instrument position of the image acquisition system;
and the image enhancement processing module is used for regarding the image as a two-dimensional signal through a frequency domain method and enhancing the signal based on two-dimensional Fourier transform.
2. The system of claim 1, wherein the display device is an LCD panel and the display device is disposed on the main body device.
3. The system of claim 1, wherein the input device comprises a keyboard and a mouse.
4. The system of claim 1, wherein the main body device further comprises an interface for connecting a printer.
5. The system of claim 1, wherein the main body device is in the shape of a cuboid or a cube.
6. A computer readable storage medium storing instructions that, when executed on a computer, cause the computer to perform a physician lung nodule auxiliary diagnosis system as claimed in any one of claims 1 to 5.
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