Analysis of ocular pathological specimen images using image analysis software
Not Applicable
Recruiting
- Conditions
- Orbital disease
- Registration Number
- JPRN-UMIN000047465
- Lead Sponsor
- Osaka Metropolitan University
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 100
Inclusion Criteria
Not provided
Exclusion Criteria
1.Patients with complications that affect the evaluation 2. Patients who have offered not to participate in this study from the published information
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Quantitative evaluation results by topological geometric method. Specifically, the ratio (b1 / b0) of the 0-dimensional Vetch number, the one-dimensional Vetch number, and the Betch number obtained from each pathological sample image, and the threshold value of the bivaluation when it is obtained. Basis for setting the main evaluation items: A method for calculating quantitative evaluation of the main outcome 1 is described. In this study, we analyze images using homology. In the analysis using homology, the vetch number of the image is an important concept. Hereinafter, the number of veches based on the definition limited to the two-dimensional image will be outlined. All pathological images in this study are two-dimensional images.
- Secondary Outcome Measures
Name Time Method 1, How does the threshold of bivalanization change when the vetch number is obtained by normal structure, inflammation and neoplastic changes? 2,The correct diagnosis rate when the identification model which distinguishes the above structure, inflammation, tumor, emphysema change from the logistics regression model and the machine learning model for multiclass classification is created.