A Performance Evaluation of a Method for Segmenting Lung Lobes Based on Tubular Tissues Density using MDCT images and its Application

Abstract

The human lung is composed of five compartments called "Lung lobes." Segmenting lung lobes from chest Multidetector-row Computed Tomography (MDCT) images can provide effective information for analyzing pulmonary conformation and detecting pulmonary diseases such as the emphysema. Our method finds the boundary surface between lung lobes by the fuzzy control that fits a curved surface into the space with lower density of tubular tissues, which are defined as peripheral blood vessels and bronchus. This paper describes the performance evaluation of the proposed method and the application method for estimating the forced vital capacity of individual lung lobes.