QUANTIFICATION OF PLEURAL EFFUSION ON CT IMAGES BY AUTOMATIC AND MANUAL SEGMENTATION

Pertab Rai,Murk Rehman

doi:10.29121/ijetmr.v6.i5.2019.375

Abstract

The objective of this research is to make reliable estimation of pleural effusion volume in CT imaging using digital image processing algorithms. In order to make reliable estimation we need to do the manual and automatic segmentation of CT images and to perform the comparison of automatic and manual segmentation for the quantification of pleural effusion on CT images which provides help in the diagnosis of the pleural disease. Pleural effusion is the collection of excess fluid in the pleural cavity. Excessive amount of fluid can impair breathing by limiting the expansion of lungs. Heart failure, cancer, cirrhosis, pneumonia, tuberculosis and many other are the causes of pleural effusion. A number of noninvasive imaging techniques such as radiography, ultrasound and computed tomography (CT) can detect the pleural effusion. The problem faced is the quantification of pleural effusion volume for the purpose of diagnosis of the pleural disease. The objective of this research is to make reliable estimation of pleural effusion volume in CT imaging using digital image processing algorithm. In order to make reliable estimation we need to do the manual and automatic segmentation of CT images and to perform the comparison of automatic and manual segmentation for the quantification of pleural effusion on CT images which provides help in diagnosis of the pleural disease. The results obtained by both the aforementioned techniques indicate that the manual segmentation is better because automated technique has less number of pixels.

Highlights

In humans and in many other animals, the main organs of the respiratory system are lungs
In order to meet with our objective the methodology was discussed in the following steps; first, the manual segmentation of the computed tomography (CT) images was done with the GNU Image Manipulation Program (GIMP) software after that the manually segmented images are processed in MATLAB to plot the histogram and probability density function (PDF) of data in order to compute the mean and standard values
Quantification of pleural effusion has been in research over several decades

Summary

Introduction

In humans and in many other animals, the main organs of the respiratory system are lungs. Each lung is surrounded by the two pulmonary pleurae (known as visceral and parietal) in which there is thin fluid filled space called pleural cavity [1]. The collection of excess fluid in the pleural cavity is called Pleural effusion. Excessive amount of fluid can impair breathing by limiting the expansion of lungs [2]. Cancer, cirrhosis, pneumonia, tuberculosis and many other are the causes of pleural effusion [3]. A number of noninvasive imaging techniques such as radiography, ultrasound and computed tomography (CT) can detect the pleural effusion [4]. CT scan or computerized axial tomography (CAT) has performed a vital role in diagnostic and therapeutic

Objectives

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Results

Conclusion