Automatic Diagnosis of Thyroid Ultrasound Image Based on FCN-AlexNet and Transfer Learning

Abstract

An automatic method applied to the thyroid ultrasound images for lesion localization and diagnosis of benign and malignant lesions was proposed in this paper. The FCN-AlexNet of deep learning method was used to segment images, and accurate localization of thyroid nodules was achieved. Then, the method of transfer learning was introduced to solve the problem of training data shortages during training process. According to the performance of AlexNet in classification, it was used to diagnose benign and malignant lesions. The localization effects of TBD, RGI, PAORGB, and ASPS methods were comparatively evaluated by IoU indicators, and the accuracy of benign and malignant diagnosis of those methods are evaluated by Accuracy, Sensitivity, Specificity, and AUC. The experimental results shown that the proposed method has better performance in localization and diagnosis of benign and malignant lesions.