Deep learning-based thyroid benign and malignant nodule area detection method

Abstract

The invention discloses a thyroid benign and malignant nodule area detection method based on deep learning, and the method comprises the steps: enabling a detection state stabilization module to be worn on the neck of a patient, maintaining a monitoring stability state, and enabling a monitoring contact point of a focus skin surface feature collection module to be in contact with a nodule focus of the patient; pathological features of a patient are detected through the focus skin surface feature collection module, the body temperature change collection module and the heart rate feature collection module. After data proportion is obtained by collecting different types of data and influence degrees of the types on illness states, a final numerical value is obtained after data correction, a reference value for judging whether the patient is good or bad in a recovery state is given to the patient, and meanwhile when the contact outer barrier layer is in displacement due to hand contact, the patient can be prevented from being damaged. Through flexible deformation, migration pulling of the back neck inner attaching layer is avoided, and then the position stability of the focus skin surface feature collecting module under collecting and capturing within a period is kept.

Description

technical field [0001] The invention relates to the field of biomedical technology, in particular to a deep learning-based detection method for benign and malignant thyroid nodule areas. Background technique [0002] In order to ensure the effective treatment of thyroid nodules, in routine inspection and treatment, instrument testing is usually used to determine the degree of benign and malignant thyroid. Give the patient a reference value for judging the good and bad in the recovery state. The patient cannot intuitively understand the changes of his nodules through a simpler data comparison. The patient's nodules appear to overlap in position, and the patient's behavior or external factors interfere with the position of the detection point due to the unconscious touch of the hand, which acts on the multi-frequency data detection and acquisition, which will cause the acquisition value to have a larger value. Accumulated tolerances, resulting in less than ideal detection sta...

AI Technical Summary

Problems solved by technology

[0002] In order to ensure effective treatment of thyroid nodules, in the routine inspection and treatment, the method of instrument detection is usually used to distinguish the benign and malignant state of the thyroid gland during the period. Give the patient a reference value for judging good and evil in the recovery state. The patient cannot intuitively understand the changes in his own nodules through a simpler data comparison. The position of the patient's nodules overlaps, and the patient's behavior or external factors interfere with the position of the detection point due to the unconscious pressure of the hand. Under the multi-frequency data detection and collection, it will cause a large difference in the collected value. Cumulative tolerances, resulting in unsatisfactory detection stability

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