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Method for detecting seven types of skin tumors for cellphone

A skin tumor and detection method technology, applied in computer parts, medical data mining, computer-aided medical procedures, etc., can solve problems such as insufficient medical resources, achieve the effect of simplifying the process and assisting doctors in diagnosis

Inactive Publication Date: 2019-03-26
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

[0007] In order to solve the serious shortage of medical resources at present, the present invention proposes a detection method for seven types of skin tumors applied to mobile phones

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  • Method for detecting seven types of skin tumors for cellphone
  • Method for detecting seven types of skin tumors for cellphone
  • Method for detecting seven types of skin tumors for cellphone

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Embodiment Construction

[0024] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0025] The hardware environment used for implementation is: CPU Intel(R) Xeon(R) CPU E5-2630v4@2.20GHz, GPU is NVIDIA K80, and the operating environment is python2.7 and TensorFlow.

[0026] The deep convolutional neural network Inception-v3 is adopted, with 47 convolutional layers, and the global average pooling layer is used to replace the fully connected layer, which is spatially decomposed into asymmetric convolution, which greatly reduces the amount of parameters and speeds up the calculation.

[0027] The excellent performance of this network is mainly due to the extensive use of dimensionality reduction processing. The convolution of large-size filters (such as 5*5, 7*7) introduces a large amount of calculations. Using two 3*3 convolutions in series instead of a 5*5 convolution can reduce the amount of calculations, and the 3 The *3 con...

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Abstract

The invention discloses a method for detecting seven types of skin tumors for a cellphone, and the method adopts an optimized Inception-v3 classification network for skin tumor images and achieves thedesired effect. The network is also suitable for other dermoscopic image detection, and a skin tumor classification method is proposed, which can detect seven types of skin tumors. The results show that the detection accuracy of the method is up to 92% higher than 75% of human eye recognition, which can effectively assist doctors in diagnosis. The present invention proposes an application development method for the detection of the seven types of skin tumors. The computer vision related knowledge is applied to people's real life, thereby simplifying the process of detecting skin tumors, and enabling doctors to obtain test results in real time simply by simply operating the application.

Description

technical field [0001] The invention relates to the field of artificial intelligence, and relates to a method for detecting seven types of skin tumors applied to mobile phones. Background technique [0002] Skin tumors are cell proliferative diseases that occur in the skin. There are many types, which are clinically divided into benign tumors and malignant tumors. Malignant tumors can continue to proliferate, cause metastasis, and threaten life, which is called skin cancer. [0003] Skin tumors are currently difficult to treat dermatological diseases, and generally refer to benign and malignant tumors that originate in the skin. Common malignant tumors in dermatology mainly include basal cell carcinoma, squamous cell carcinoma, and malignant melanoma. The incidence rates of the three malignant tumors are increasing year by year, seriously affecting the health of patients and even threatening their lives. The seven types of tumors that can be identified in the present inve...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G16H50/70G06N3/04G06K9/62
CPCG16H50/20G16H50/70G06V2201/032G06N3/045G06F18/24G06F18/214
Inventor 端阳马恺强孙玲玲
Owner HANGZHOU DIANZI UNIV
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