Lung Parenchyma Segmentation from CT Images with a Fully Automatic Method

For the last three years, the world has been facing an infectious disease that primarily affects the human breathing organ. The disease has caused many deaths worldwide so far and has imposed high economic costs on all countries. Therefore, attention to computer-aided detection/diagnosis (CAD) systems to help diagnose and treat diseases related to the human respiratory system should be given more attention so that countries' health systems can treat patients in epidemics. Considering the importance of CAD systems, we proposed a two-step automatic algorithm. In the first step, we obtain the primary boundary of the lobes in CT lung scan images with the help of some conventional image processing tools. In the second stage, we obtained a more precise boundary of the lung lobes by correcting the unusual dimples and valleys (which are sometimes caused by the presence of juxtapleural nodules). This proposed method has low implementation time. Given that a precise boundary of the pulmonary lobes is essential in the more accurate diagnosis of lung-related diseases, an attempt has been made to ensure that the final segmentation of the lung parenchyma has an acceptable score in terms of evaluation criteria so that the proposed algorithm can be used in the diagnosis procedure.

Automated summary

For the past three years, the world has been dealing with an infectious disease that primarily affects the human respiratory system, causing numerous deaths and significant economic losses globally. Therefore, there is a need for more attention to computer-aided detection/diagnosis (CAD) systems to assist in diagnosing and treating respiratory-related diseases, enabling healthcare systems to better handle epidemic situations.