Tranform-based thyroid nodule detection method

Abstract

The invention discloses a thyroid nodule detection method based on Transform, and relates to the technical field of image processing, and the method comprises the steps: obtaining a to-be-detected ultrasonic image of a thyroid region, carrying out the image preprocessing of the obtained to-be-detected ultrasonic image, inputting the to-be-detected ultrasonic image into a nodule detection model which is obtained through the training based on a Transform network in advance, and obtaining a nodule detection model; according to the output of the nodule detection model, determining the position and type of the nodule in the to-be-detected ultrasonic image, and completing the detection of the nodule in the to-be-detected ultrasonic image, the nodule type being used for indicating that the nodule is a benign nodule or a malignant nodule; the method can automatically complete positioning and classification of nodules, is high in automation degree and good in objectivity, does not need to construct a dense Anchor Box, does not need to use NMS complex post-processing operation, is easy to implement, and has low requirements for computing resources.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a Transformer-based thyroid nodule detection method. Background technique [0002] Thyroid tumors are common and multiple tumors of the head and neck. In recent years, the incidence of thyroid cancer has been increasing year by year, which has attracted extensive attention from clinicians and researchers. Some thyroid nodules are highly malignant, so early diagnosis and treatment of thyroid nodules can effectively prevent thyroid cancer. In clinical practice, ultrasound is generally used to examine the thyroid gland. Ultrasound examination is an imaging examination method widely used in modern clinics. It can obtain information such as the boundary, shape, and echo of thyroid nodules in patients, and provide support for further treatment of patients with thyroid nodules. . However, at present, domestic medical resources are tight, and the number of experienced ultraso...

AI Technical Summary

Problems solved by technology

[0004] In the existing technical solutions, both methods have the following disadvantages: (1) Anchor Boxes with different aspect ratios and different sizes need to be set before the experiment

However, due to the fact that the size of the input thyroid ultrasound image is not fixed and the size of the nodule area in the image is different, the hyperparameters such as the size, aspect ratio, and number of the Anchor Box will have a great impact on the experimental results. The process of auxiliary diagnosis is facing a huge test

(2) In order to bring a higher recall rate to the experimental results, a large number of dense Anchor Boxes are often set in an image, but the number of nodules in each thyroid ultrasound image is very small, and a large number of Anchor Boxes The category division in the training phase will bring about a huge imbalance between positive and negative sample categories, and the calculation of IoU in the training and testing phase will increase the amount of calculation and consume memory resources.

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