Evaluation of Selected Two-Dimensional Segmentation Techniques for Computed Tomography Quantitation of Lymph Nodes

Abstract

As contrast agents that selectively target normal lymph nodes are undergoing development and evaluation, it has become important to accurately and reproducibly determine nodal boundaries to study the agents and determine such values as lymph node area or mean nodal contrast concentration. This study was performed to evaluate the accuracy of different two-dimensional computer segmentation methods, tested on acrylic phantoms constructed to imitate the appearance of lymph nodes surrounded by fat. Five segmentation techniques (manual tracing, semiautomatic local criteria threshold selection, Sobel/watershed technique, interactive deformable contour algorithm and thresholding) were evaluated using phantoms. Subsequently, the first three methods were applied to the images of enhanced lymph nodes in rabbits. Minimum errors in phantom area measurement (< 5%) and interoperator variation (< 5%) were seen with the Sobel/watershed technique and the interactive deformable contour algorithm. These two techniques were significantly better than thresholding and semiautomated thresholding based on local properties. Methods based on Sobel edge detection offer more objective tools than thresholding methods for segmenting objects similar to lymph nodes in computed tomography images. Both methods, Sobel/watershed and interactive deformable contour algorithm, are fast and have simple user interfaces.