Thyroid Nodule Detection in Ultrasound Images with Convolutional Neural Networks

Thyroid tumor is a common clinical disease. Fully automated computer-aided diagnosis of thyroid nodules has important clinical significance. However, most of the previous works focused on the classification of nodules, benign or malignant, but how to locate the nodules in the ultrasound images is rarely studied. This paper focuses on the problem of thyroid nodule detection, aiming to achieve a fully automated method for delineating the nodule bounding box from the thyroid ultrasound image. We propose a nodule detection algorithm based on the convolutional neural network for this task. We explore the performance of nodule detection in three aspects: multi-scale prediction architecture design, loss function design and postprocessing method. This method is evaluated on clinical data and compared to the ground truth labeled by doctors. The experimental results show that this proposed method can achieve 88.08 % AP with 90.08 % overall recall.