Knowledge Bank

Goal: To determine the feasibility of utilizing image segmentation to evaluate axillary lymph nodes with both automatic and manual technology. Methods: Manual technology was accomplished with GE Logic 9 ultrasound machine, 3D volume set, and Vocal software. The automated technology was accomplished by uploading the volume sets to a computer with software that provides the ability to perform level set algorithms, active contours, deformable models, thresholding, and region growing and ultimately creates a segmented model of the node. Findings: Manual image segmentation provides smooth cortical borders on all nodes imaged. It is feasible to conduct automated segmentation of sonographic images from 3D rendered images of axillary lymph nodes. However automatic image segmentation provides textured borders that include afferent lymph vessels and aging changes. Cubic volume sets of each node for each type of segmentation have been calculated to be compared to each other as well. Significance: Automated image segmentation demonstrates early utility in determining precise cortical morphology of the node. This may be beneficial for assessing signs of detection of breast cancer. This research also furthers the idea that sonography can be used as a non-invasive, non-ionizing modality to manually and automatically segment lymph nodes. Continued research with image segmentation can promote a standard way to assess axillary lymph nodes and obtain precise tissue volumes and diagnosis.