Segmentation of Lung Lobes and Fissures for Surgical Pre Planning

Abstract

Medical imaging is the technique that is used to create images of the human body or parts for clinical purposes (medical procedures seeking to reveal diagnose or examine disease). The CT images provide detailed information of anatomy of lungs, which could be used for better surgical planning of treating Lung Cancer This Work, proposes a method for Segmentation of Lung lobes and fissures for surgical planning of treating Lung Cancer. This work presents a ‘lobe and fissure’ segmentation algorithm that uses a two stage approach. This work presents a threshold based lobe segmentation algorithm. Modified adaptive fissure sweeping and Wavelet Transform are used to segment Lung fissures in CT images. The unseen or partially seen fissures are enhanced and segmented. The main modules of this work are Preprocessing, Lung Segmentation by Iterative Threshold method, Fissure Region Sweeping, Wavelet Transform, Otsu’s binarization, Fissure verification, Interpolation and Extension of Fissures. In the Preprocessing work noises are reduced. The preprocessing is done by fuzzy filter. In the next module lung area are segmented by Iterative Threshold Method. Then the fissure regions are collected. Next Wavelet Transform generates the features. Then Otsu’s method is adopted for binarization. Next Interpolation is done and fissure is extended up to needed length. Finally Fissure information are extracted and displayed.