Advanced Healthcare Systems

5Methods of Lung Segmentation Based on CT Images

Amit Verma^* and Thipendra P. Singh

School of Computer Science, UPES, Dehradun, Uttarakhand, India

Abstract

Considering the ground truth of most of the hospitals, today, also the doctors are manually observing the computed tomography (CT) images of lungs based on their experience and knowledge. CT images of lungs have major applications in the analysis of functioning, structure, and many more information about the pulmonary images. Lung airways, parenchyma of lungs, and breathing mechanism are majorly analyzed on the basis of CT images. So, for better analysis and to avoid manual method of analysis of CT images by the doctor, automatic and almost accurate analysis of CT images is very important for better diagnosis for any lung problem. In this chapter, automatic and semi-automatic methods of segmentation of lungs CT images are discussed.

Keywords: Segmentation, CT image, machine learning, medical image, lung, seed pixel, knowledge-based

5.1 Introduction

Image segmentation is the process of dividing an image into multiple parts according to the interest, as it is less efficient to analyze the whole image despite analyzing the interesting part of the image only. Segmentation helps to analyze the particular area of the image in a much better way [1]. The main objective of any segmentation technique is to make images more informative and useful for the analyst.

Therefore, segmentation plays a vital role in investigating the pulmonary ...