Preliminary Study on Eye Features of Patients With Malignant Tumors

Application of White Eye Imaging Health Care System on Diagnosis of Malignant Tumors

Based on the theory of traditional Chinese Medicine, this study collects eye features of white eyes through the White Eye Imaging Health Care System under visible light and establishes a database of eye-eye features corresponding to the disease. The computer image analysis and artificial intelligence technology are used to visualize the eye. The features were extracted and classified, and the corresponding changes in the characteristics of the traditional Chinese medicine and the disease were analyzed statistically to establish an analytical model corresponding to the disease.

1. Collecting the white-eyed eye features of 500 patients with malignant tumors and 500 non-tumor patients by the white-eye shadowless imaging acquisition system under visible light, and establishing eye-catching images of malignant tumor patients and healthy people of different diseases. Feature database.
2. Based on the collected four-dimensional eye-eye diagram, using computer image analysis and artificial intelligence technology to extract and classify the eye-eye features of the white eye, and statistically analyze the correlation between the eye-eye features and the malignant tumor. The relationship between the characteristics of the white eye and the corresponding change of malignant tumor.

Inclusion Criteria:

• Malignant tumor patients with clear pathological diagnosis;

  • Those who have no serious primary diseases of the cardiovascular, cerebrovascular, respiratory, endocrine, urinary, blood and other systems;

    • The main organs (hematopoiesis, heart, lung, liver, and kidney) have no obvious abnormal function; ④Age ≥18 years old, ≤75 years old; ⑤ No serious eye disease;

      • The patient volunteered to participate in this study.

Exclusion Criteria:

• Patients with severe blood loss (because when the bleeding exceeds 300ml, the white eye color of the patient is often pale white);

  • Poor patient compliance; ③ pregnant and lactating women;

    • Can't cooperate with inspection properly; ⑤ Cannot read or understand the scale.