摘要
A method of removing the airway from pulmonary segmentation image was proposed. This method firstly segments the image into several separate regions based on the optimum threshold and morphological operator, and then each region is labeled and noted with its mean grayscale. Therefore, most of the non-lung regions can be removed according to the tissue’s Hounsfield units (HU) and the imaging modality. Finally, the airway region is recognized and deleted automatically through using the priori information of its HU and size. This proposed method is tested using several clinical images, yielding satisfying results.
A method of removing the airway from pulmonary segmentation image was proposed. This method firstly segments the image into several separate regions based on the optimum threshold and morphological operator, and then each region is labeled and noted with its mean grayscale. Therefore, most of the non-lung regions can be removed according to the tissue's Hounsfield units (HU) and the imaging modality. Finally, the airway region is recognized and deleted automatically through using the priori information of its HU and size. This proposed method is tested using several clinical images, yielding satisfying results.
