Image Segmentation of Thyroid Nodule and Capsule for Diagnosing Central Compartment Lymph Node Metastasis

Thyroid ultrasound (US) image segmentation is of great significance for both doctors and patients. However, it is a challenging task because of the low image quality, low contrast and complex background in each US image. In recent years, some researchers have done thyroid nodule segmentation tasks, but the results achieved are not particularly satisfactory. In this paper, we have broadened the targets of interest and included both thyroid nodules and capsules into our research scope. We propose a method that implements a C-MMDetection to detect and extract the region of interest (ROI), and a modified salient object detection network U²-RNet to segment nodules and capsules respectively. Experiments show that our method segments nodules and capsules in US images more effectively than other networks, which is very helpful for doctors to diagnose central compartment lymph node metastasis (CLNM).