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Manifold learning-based pulmonary nodule case matching auxiliary detection system and working method thereof

A technology for auxiliary detection and case matching, applied in computer-aided medical procedures, informatics, medical informatics, etc., can solve the problems of noise sensitivity, no consideration of patients, manual giving, etc.

Inactive Publication Date: 2017-06-27
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This patent has the following defects: the main idea of ​​this patent is to use the segmentation method of the region growing method to segment, and the disadvantage is that each area to be extracted must manually give a seed point, so that if there are multiple areas, the corresponding The number of seeds, this method is very sensitive to noise, resulting in many regions that are not continuous at all
And this method is only an auxiliary detection, from the doctor's point of view, does not consider the patient itself

Method used

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  • Manifold learning-based pulmonary nodule case matching auxiliary detection system and working method thereof
  • Manifold learning-based pulmonary nodule case matching auxiliary detection system and working method thereof
  • Manifold learning-based pulmonary nodule case matching auxiliary detection system and working method thereof

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Embodiment 1

[0069] A case-matching auxiliary detection system for pulmonary nodules based on manifold learning, such as figure 1 As shown, it includes a case collection module, a case classification and storage module, a case matching module, a case judgment module and a case correction module, and the case collection module, case classification and storage module, case matching module, case judgment module and case correction module are sequentially ring connection;

[0070] The case collection module obtains the case database by collecting lung CT pictures captured by the CT medical imaging system and patient information entered by the electronic medical record system. The case database includes patient information and one or more lung CT pictures corresponding to the patient ; The patient information includes the patient's name, gender, age, home address, time of illness, and the CT picture includes medical symptoms, diagnostic results and treatment measures of pulmonary nodules; the m...

Embodiment 2

[0085] The working method of the pulmonary nodule case matching auxiliary detection system described in embodiment 1, such as Figure 5 shown, including the following steps:

[0086] (1) The doctor logs into the pulmonary nodule case matching auxiliary detection system based on manifold learning, and inputs the currently captured lung CT image into the t-SNE calculation framework;

[0087] (2) The doctor inputs the value of the threshold value radius A and the value of the number N of recommended cases, and the case matching module screens and matches the current case with the case classification and the case library built by the storage module to provide N recommended cases, the current case That is, the lung CT picture currently taken as described in step (1); image 3 As shown, the specific steps include:

[0088] a. Perform the first screening and matching, and the first screening and matching unit will be marked (add the current case to the previously prepared case coll...

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Abstract

The invention relates to a manifold learning-based pulmonary nodule case matching auxiliary detection system and a working method thereof. The method comprises the steps that firstly, a case needing to be judged is marked and input a t-SNE computing framework of a text together with a formed case library, a two-dimensional embedding graph is formed through manifold learning, and other cases in a circle with the radius smaller than A are found in the two-dimensional embedding graph by taking the current case as a core and taking a threshold value A as the radius; secondly, the Euclidean distances between the other cases in the circle with the radius smaller than A and the current case are computed, and computing results are sorted; finally, the first N cases which have the smallest Euclidean distances with the current case are selected as recommended cases to be recommended to a doctor. The extraction method has the advantages of being high in recommended case precision and matching speed.

Description

technical field [0001] The invention relates to a pulmonary nodule case matching auxiliary detection system based on manifold learning and a working method thereof, and belongs to the technical field of pulmonary nodule case matching auxiliary detection systems. Background technique [0002] In the process of doctors diagnosing benign and malignant pulmonary nodules in CT images, doctors will outline the pulmonary nodules contained in CT images and the medical symptoms of these pulmonary nodules, and finally, different medical symptoms, diagnostic results and corresponding symptoms will be formed. These data are the accumulation of doctor's experience and knowledge. Establishing these valuable experience and knowledge accumulation into a case database associated with the electronic medical record management system will help to improve the existing electronic medical record management and improve various data. The data provide a powerful case base for follow-up diagnosis of p...

Claims

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Application Information

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IPC IPC(8): G06F19/00G06F17/30
CPCG06F19/325G06F16/583G06F16/5866G06F19/321G16H50/70
Inventor 杨阳李夏刘云霞熊海良
Owner SHANDONG UNIV
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