Construction method of gastrointestinal stromal tumor malignant potential classification model based on support vector machine

A technology of support vector machine and gastrointestinal stromal tumor, which is applied in the fields of oncology, machine learning, and imaging, can solve the problem that the application value needs to be improved, and achieve the effect of avoiding damage and reducing the error rate.

Inactive Publication Date: 2017-12-19
NANFANG HOSPITAL OF SOUTHERN MEDICAL UNIV
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, although the existing GIST classification methods can provide a certain reference

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Construction method of gastrointestinal stromal tumor malignant potential classification model based on support vector machine
  • Construction method of gastrointestinal stromal tumor malignant potential classification model based on support vector machine
  • Construction method of gastrointestinal stromal tumor malignant potential classification model based on support vector machine

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] 1. Data collection

[0021] (1) Specified criteria: For example, patients with (a) GIST patients who have not received adjuvant imatinib therapy (b) GIST patients who have undergone complete resection (c) patients with abdominal enhanced CT less than 15 days before surgery. The influence of other factors on this experiment was excluded.

[0022] (2) Abdominal contrast-enhanced CT images of GIST patients included in the analysis; randomly divided into training group and prediction group according to 4:1.

[0023] (3) To test whether the differences caused by potential influencing factors such as age, sex, tumor primary site, and histological grade between the two groups of patient data are statistically significant.

[0024] 2. Extract and filter features:

[0025] Use the ITK-SNAP software to outline the ROI, draw the outline of the tumor layer by layer, and perform three-dimensional volume reconstruction on the two-dimensional ROI to generate a VOI (such as figure ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention belongs to the fields such as oncology, iconography and machine learning, and relates to a construction method of a gastrointestinal stromal tumor malignant potential classification model based on a support vector machine. The construction method according to the invention comprises the steps of data acquisition, namely performing thin-layer CT image acquisition in a belly reinforcing period; extracting and screening a characteristic; obtaining a punishment parameter and a kernel function parameter through cross validation; establishing a classification model through the parameters; and checking model classification performance. The classification model which is constructed according to the method and is based on the support vector machine can accurately classify the gastrointestinal stromal tumor to two kinds, namely a low malignant potential kind and a high malignant potential kind. Furthermore the classification model is based on an existing image resource and does not cause an additional cost of a patient, thereby facilitating clinical popularization.

Description

technical field [0001] The invention belongs to the fields of oncology, imaging, machine learning and the like, and relates to a method for constructing a support vector machine-based malignant potential classification model of gastrointestinal stromal tumors. Background technique [0002] Gastrointestinal stromal tumors (Gastrointestinal Stromal Tumors, GIST) are a type of tumor originating from the stromal tissue of the gastrointestinal tract, accounting for most of the gastrointestinal mesenchymal tumors. Gastrointestinal stromal tumors have malignant potential, but the classification of their malignant potential has always been a difficult problem for clinicians. [0003] Currently, there are two main classification methods for GIST: modified NIH and AFIP. Both the modified NIH and AFIP include the three parameters of tumor maximum diameter, mitotic count and tumor site, and the modified NIH also includes the parameter of tumor rupture. In terms of clinical operation, ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/62G06T7/00G06T7/12
CPCG06T7/0012G06T7/12G06T2207/10081G06T2207/30096G06T2207/20104G06T2207/20116G06F18/2411
Inventor 陈韬李国新卢振泰祁小龙
Owner NANFANG HOSPITAL OF SOUTHERN MEDICAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap