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Tumor detection method based on Raman spectrum and convolutional neural network

A convolutional neural network and Raman spectroscopy technology, applied in the field of medical data detection, can solve the problems of pathological biopsy with many steps, biopsy time affecting surgical efficiency, and long analysis time, so as to improve timeliness and accuracy and avoid canceration Effects of organizational diffusion and workload reduction

Pending Publication Date: 2021-01-08
SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
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Problems solved by technology

However, there are many steps in pathological biopsy, long analysis time, and the accuracy and sensitivity of intraoperative biopsy techniques are not reliable. In order to ensure the complete resection of tumor tissue, multiple pathological biopsies are required. The long biopsy time not only affects the operation efficiency, but also risks to patients

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  • Tumor detection method based on Raman spectrum and convolutional neural network
  • Tumor detection method based on Raman spectrum and convolutional neural network
  • Tumor detection method based on Raman spectrum and convolutional neural network

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[0035] In order to further understand the present invention, a tumor detection method based on Raman spectroscopy and convolutional neural network provided by the present invention will be described in detail below in conjunction with specific embodiments, but the present invention is not limited thereto. Non-essential improvements and adjustments made under the guiding ideology still belong to the protection scope of the present invention.

[0036] A tumor detection method based on Raman spectroscopy and convolutional neural network, including:

[0037] Data set collection and construction, obtain a large number of Raman spectrum data sets, and use high-resolution CCD Raman spectrum detection equipment to detect the normal tissue parts and tumor tissue parts of tumor patients respectively. The detection is carried out by Raman fiber optic probes. Different Raman spectra are formed by excitation, and the Raman spectra are divided into a training set and a test set according to...

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Abstract

The invention belongs to the technical field of medical data detection, and particularly relates to a tumor detection method based on a Raman spectrum and a convolutional neural network. The inventiondiscloses a tumor detection method based on a Raman spectrum and a convolutional neural network. The tumor detection method comprises the following steps: S1, collecting and constructing a data set;s2, carrying out data set standardization processing; s3, carrying out data set amplification; s4, training a classification model; and s5, carrying out tumor prediction. The tumor detection method based on the Raman spectrum and the convolutional neural network is rapid, convenient and accurate, and aims to solve the technical problems that pathological biopsy steps of tumor tissue sections are numerous, long in time and general in accuracy in a tumor excision operation.

Description

technical field [0001] The invention belongs to the technical field of medical data detection, and in particular relates to a tumor detection method based on Raman spectrum and convolutional neural network. Background technique [0002] Clinically, the location of the tumor tissue is usually determined by imaging examinations to guide the design of the resection operation plan, such as the use of endoscopy, CT, nuclear magnetic resonance, X-ray and other technical means. However, the time difference between imaging examination and resection will lead to deviations between the image data and the tumor tissue outline, location, size and other information seen in the actual operation. Pathological biopsy of tissue sections is usually used during resection surgery to determine whether the tumor tissue has been completely resected. However, there are many steps in pathological biopsy, long analysis time, and the accuracy and sensitivity of intraoperative biopsy techniques are no...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0012G06T2207/20081G06T2207/20084G06T2207/30096G06F18/24G06F18/214
Inventor 吴健俞洪蕴曹政
Owner SHANDONG IND TECH RES INST OF ZHEJIANG UNIV
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