Adaptive Order Polynomial Fitting for Pulmonary Nodule Segmentation in Chest Radiograph

Segmentation of pulmonary nodules in chest radiographs is a particularly challenging task due to heavy noise and superposition of fibs, vessels, and other complicated anatomical structures in lung field. In this paper, an adaptive order polynomial fitting based ray- casting algorithm is proposed for pulmonary nodule segmentation in chest radiographs. Instead of detecting nodule edge points directly, the nodule intensity proffies are first fitted by using the polynomials with adaptively determined orders. Then, the edge positions are identified through analyzing the local minimum of the fitted curves. The performance of the proposed algorithm was evaluated over an image database with 148 nodule cases in chest radiographs that were collected from a variety of digital radiograph modalities. The preliminary results show the proposed algorithm can obtain a high rate of successful segmentations.