Chronic obstructive pulmonary disease detection system based on deep neural network
A deep neural network and chronic obstructive technology, applied in the field of neural network, can solve the problem of inaccurate detection results of COPD detection system, and achieve the effect of improving accuracy
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment 1
[0041] figure 1 It is a schematic diagram of a detection system for chronic obstructive pulmonary disease based on a deep neural network according to an embodiment of the present invention, such as figure 1 As shown, the embodiment of the present invention provides a COPD detection system based on a deep neural network, including a preprocessing module 10 and a detection module 20, wherein,
[0042] The preprocessing module 10 is configured to perform grayscale processing on the acquired chest CT image of the first patient, and extract a plurality of lung lobular region images in the chest CT image after grayscale processing;
[0043] The detection module 20 is used to input the acquired body mass index (BMI) of the first patient and the images of the plurality of pulmonary lobular regions into the trained deep neural network model to obtain the information of the first patient suffering from chronic obstructive pulmonary disease. probability value.
[0044] Further, the dee...
Embodiment 2
[0077] figure 2 A schematic structural diagram of an electronic device for COPD detection provided by an embodiment of the present invention, such as figure 2 As shown, the device includes: a processor (processor) 801, a memory (memory) 802 and a bus 803;
[0078] Wherein, the processor 801 and the memory 802 complete mutual communication through the bus 803;
[0079] The processor 801 is used to call the program instructions in the memory 802 to perform the following steps:
[0080] performing grayscale processing on the acquired chest CT image of the first patient, and extracting images of a plurality of pulmonary lobular regions in the chest CT image after grayscale processing;
[0081] Inputting the obtained BMI of the first patient and the images of the plurality of pulmonary lobular regions into the trained deep neural network model to obtain the probability value of the first patient suffering from chronic obstructive pulmonary disease.
Embodiment 3
[0083] An embodiment of the present invention discloses a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, The computer is capable of performing the following steps:
[0084] performing grayscale processing on the acquired chest CT image of the first patient, and extracting images of a plurality of pulmonary lobular regions in the chest CT image after grayscale processing;
[0085] Inputting the obtained BMI of the first patient and the images of the plurality of pulmonary lobular regions into the trained deep neural network model to obtain the probability value of the first patient suffering from chronic obstructive pulmonary disease.
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com