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http://www.iaeme.com/IJEET/index.asp 7 [email protected] International Journal of Electrical Engineering & Technology (IJEET) Volume 11, Issue 2, March-April 2020, pp. 7-16, Article ID: IJEET_11_02_002 Available online at http://www.iaeme.com/IJEET/issues.asp?JType=IJEET&VType=11&IType=2 ISSN Print: 0976-6545 and ISSN Online: 0976-6553 Journal Impact Factor (2020): 10.1935 (Calculated by GISI) www.jifactor.com © IAEME Publication DETECTION OF LUNG CANCER USING IMAGE SEGMENTATION V. Kannan Professors, Department of ECE, GMR Institute of Technology, Rajam, Andhra Pradesh, India V. Jagan Naveen Professors, Department of ECE, GMR Institute of Technology, Rajam, Andhra Pradesh, India ABSTRACT In modern days, image processing methods are widely adopted in the medical field for enhancing the earlier detection of certain abnormalities, such as the breast cancer, lung cancer, brain cancer and so on. This paper mainly concentrates on the segmentation of lung cancer tumors from X-ray images, Computed Tomography (CT) images and MRI images. Image processing methods are adopted in segmenting the images. In the pre-processing stage mean and median filters are used. In the image segmentation stage, Otsu's thresholding and k-Means clustering segmentation approaches are used to segment the lung images and locate the tumors. To evaluate the performance of the methods used for segmentation, the performance evaluation parameters such as Signal to noise Ratio(SNR) ,Mean Square Error (MSE) and Peak Signal Noise to Ratio (PSNR)) are computed on the segmented images of the two different segmentation methods used for segmentation. Better results are obtained for the K-Means segmentation irrespective of the images. Keywords: Lung Cancer, Computed Tomography, MRI, Thresolding, K-Means Clustering, MSE, PSNR Cite this Article: V. Kannan and V. Jagan Naveen, Detection of Lung Cancer using Image Segmentation, International Journal of Electrical Engineering & Technology, 11(2), 2020, pp. 7-16. http://www.iaeme.com/IJEET/issues.asp?JType=IJEET&VType=11&IType=2 1. INTRODUCTION In the modern world, there is an increase in Lung cancer which is due to abnormal multiplication of certain cell multiplying and growing into tumor. Maximum cancers that begin within the lungs are called carcinomas. Two kinds of cancers are observed as small-cell lung carcinoma and nonsmall - cell lung carcinoma [1].Tobacco smoking for long years is the primary cause for 85% of lung cancers [2]. Approximately 1015% of cases arise in humans who never smoked, but the illness is due to air pollution, 2nd hand smoking, asbestos, radon

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http://www.iaeme.com/IJEET/index.asp 7 [email protected]

International Journal of Electrical Engineering & Technology (IJEET)

Volume 11, Issue 2, March-April 2020, pp. 7-16, Article ID: IJEET_11_02_002

Available online at http://www.iaeme.com/IJEET/issues.asp?JType=IJEET&VType=11&IType=2

ISSN Print: 0976-6545 and ISSN Online: 0976-6553

Journal Impact Factor (2020): 10.1935 (Calculated by GISI) www.jifactor.com

© IAEME Publication

DETECTION OF LUNG CANCER USING IMAGE

SEGMENTATION

V. Kannan

Professors, Department of ECE,

GMR Institute of Technology, Rajam, Andhra Pradesh, India

V. Jagan Naveen

Professors, Department of ECE,

GMR Institute of Technology, Rajam, Andhra Pradesh, India

ABSTRACT

In modern days, image processing methods are widely adopted in the medical field

for enhancing the earlier detection of certain abnormalities, such as the breast cancer,

lung cancer, brain cancer and so on. This paper mainly concentrates on the

segmentation of lung cancer tumors from X-ray images, Computed Tomography (CT)

images and MRI images. Image processing methods are adopted in segmenting the

images. In the pre-processing stage mean and median filters are used. In the image

segmentation stage, Otsu's thresholding and k-Means clustering segmentation

approaches are used to segment the lung images and locate the tumors. To evaluate

the performance of the methods used for segmentation, the performance evaluation

parameters such as Signal to noise Ratio(SNR) ,Mean Square Error (MSE) and Peak

Signal Noise to Ratio (PSNR)) are computed on the segmented images of the two

different segmentation methods used for segmentation. Better results are obtained for

the K-Means segmentation irrespective of the images.

Keywords: Lung Cancer, Computed Tomography, MRI, Thresolding, K-Means

Clustering, MSE, PSNR

Cite this Article: V. Kannan and V. Jagan Naveen, Detection of Lung Cancer using

Image Segmentation, International Journal of Electrical Engineering & Technology,

11(2), 2020, pp. 7-16.

http://www.iaeme.com/IJEET/issues.asp?JType=IJEET&VType=11&IType=2

1. INTRODUCTION

In the modern world, there is an increase in Lung cancer which is due to abnormal

multiplication of certain cell multiplying and growing into tumor. Maximum cancers that

begin within the lungs are called carcinomas. Two kinds of cancers are observed as small-cell

lung carcinoma and nonsmall - cell lung carcinoma [1].Tobacco smoking for long years is the

primary cause for 85% of lung cancers [2]. Approximately 10–15% of cases arise in humans

who never smoked, but the illness is due to air pollution, 2nd hand smoking, asbestos, radon

V. Kannan and V. Jagan Naveen

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fuel and so on. X-Ray imaging and Computer tomography (CT) are the traditional techniques

to discover the affected lungs with cancer. The detection is done through biopsy that is

commonly performed with the aid of bronchoscopy or CT scan. The cause of cancer-

associated loss of life amongst men is specifically due to lung cancer. For this reason, it is

crucial to determine a new strong method to diagnose the lung cancers at an earlier stage [3].

Lung cancer, also known as lung carcinoma, is a malignant tumor characterized with the aid

of out of control growth of the tissue cells of the lungs. It is compulsory to treat this cancer to

avoid spreading in to other parts of the body [5].

Cancer cells may be carried away from the lungs through blood, or lymph fluid that

surrounds the tissues of lungs. Lymph fluid flows through lymphatic vessels and get drained

into lymph nodes positioned inside the lungs and at the center of the chest. Lung cancers

frequently spreads towards the center of the chest due to the fact that the herbal drift of lymph

fluid flows out of the lungs is towards the center of the chest. Progression takes place when

the cancerous cell leaves the site where it is originated and moves into a lymph node or to any

other a part of the body via the blood circulation [4]. Cancerous tumor that got developed

within the lung is referred to as primary lung cancer.

CT and X-rays are the traditional techniques to detect the existence of lung cancers. The

scanning is confirmed by using biopsy, that is generally finished by using bronchoscopy or

CT experiment. The reason of most cancers-associated demise among men is specifically due

to lung cancers.

1.1. Lungs and Lung Cancer

Lungs consists of two parts as right lung and left lung within the chest. The right lung consists

of 3 sections and they are called lobes. The left lung has 2 sections [6-8]. The right lung is

bigger and the left lung is smaller in order to give space for the heart. Trachea is the wind pipe

which takes air in to the lungs during breathing through nose or mouth. The trachea gets

separates into tubes known as bronchi. The bronchi which go into the lungs is further

separated into smaller bronchi. These smaller branches are called as bronchioles. At the edge

of the bronchioles, minute air sacs are present called as alveoli. During breathe in the alveoli

absorb oxygen into the blood and removes carbon dioxide from the blood while breathe out.

Since the primary function of the lungs is to mix the oxygen in to the blood and removes

carbon dioxide from it. Lung cancers usually start from the cells backing the bronchi and from

the bronchioles or alveoli of the lungs.

Figure 1 Anatomy of Human Lungs

A protecting sheath surrounds the lungs known as the pleura which protects the lungs.

This pleura assists the lungs to move backward and forward towards the chest wall during

breathing. A slim, dome-shaped muscle present under the lungs, which separates the chest and

Detection of Lung Cancer using Image Segmentation

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the abdomen is called diaphragm. During breathing, the air is forced in and out of the lungs by

the up and down movement of the diaphragm.

Most cancers begin, when there is an abnormal growth of cells in the body. A form of

cancer that is found in the lungs are called Lung cancers. The two major types of lung cancer

are small cell lung cancers and Non-small cell lung cancers (NSCLC).It is found that 85% of

the lung cancers are NSCLC [9-10]. The NSCLC are further classified as large cell

carcinoma, adenocarcinoma and squamous cell carcinomas.

Adenocarcinomas start in the cells that secrete typical substance along with mucus [11].

Lung cancers are diagnosed mostly with people who smoke [12]. Lung cancers are also

visible in people who do not smoke [13] which is due to second hand smoking. It is more

common in ladies whose husbands smoke.

Adenocarcinoma occurs in the exterior of the lung and it may be detected before it

spreads. Squamous cells are flat cells that rim the inner way of the airways within the lungs.

The cancer occur in it is called as Squamous cell carcinomas. This cancer is mostly related to

the his-tory of smoking. Any part of the lung may be affected by large cell carcinoma. It is a

dangerous cancer which may develop and spread quickly, making the treatment tougher.

Large cell neuroendocrine carcinoma is a subtype of large cell carcinoma, which is a quick-

growing lung cancer. The cancer that start form the lung only is called as lung cancer .The

cancers which spread from different organs like breast, kidney and pancreas to the lungs are

not lung cancers [14].

1.2. Causes of Lung Cancer

The main cause of present days deaths are due to Lung cancers in both women and men. To-

day, nine out of 10 lung cancer deaths are caused by smoking. The various causes of lung

cancers are discussed below

1.2.1. Smoking

Cigarettes [15] are packed with cancer-inflicting chemical substances. In addition they spoil

the lungs' natural protection system. To protect the lungs, the airways of the lungs are lined

with tiny hairs known as cilia. They sweep out pollution, bacteria, and viruses from the air

while breathing. The cilia is affected by the tobacco smoke and stops working in doing its job.

This is the main reason for the cancer-causing chemicals to build up in the lungs and. the

cancers starts quietly. During the early stages, no symptoms or warning are found due to

cancer .But when it get worse, the following symptoms may be noticed

Chest pain, during deep breathing

Cough that won't go away

Bloody phlegm when Coughing

Wheezing or shortness of breath,

Fatigue

1.2.2. Second hand Smoke

Even though the main cause of lung cancers is smoking, breathing in the second hand smoke

released by a smoker is also danger. This second hand smoke which occur at domestic or at

work place also may increase the risk of danger [16- 17]. It is found that woman‟s who are

married to a smoking person are 20% to 30% more likely to get lung cancer when compared

the woman‟s of non-smokers.

1.2.3. Risky work

Some of the working environments may also be the cause of lung cancers . People who are

working with the metals such as uranium, arsenic, and other chemical substances have more

V. Kannan and V. Jagan Naveen

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chances for cancer and they should try to limit their exposure with such metals. People work-

ing with asbestos, for insulation, may also prone to lung cancer.

1.2.4. Radon Gas

This natural radioactive gas [18-20] which can build up inside the houses may increase the

risk of lung cancers. It is found to be the second leading cause of lung cancer in some

countries. This gas can‟t be smelt or seen, but the presence of it can be identified using test

kit.

1.2.5. Air Pollution

Air pollution is also a cause for cancer, but it less prone when compared to smoking, but for

good health it is better to avoid air pollutants [21-23]. It is found that pollutants from vehicles,

power plants and factories also affect the lungs like second hand smoke does. Also it is cited

that each and every car corporation is producing minimum of two hundred Cars per day in

India which adds air pollution.

2. EARLY DETECTION OF LUNG CANCERS

The method used to check or discover a disorder in an individual, when there is no signs and

symptoms is called Screening. Initially X-Rays were studied for lung cancer screening. In

recent years, CT test, MRI test has been taken to find people at a higher risk of getting lung

cancer [24]. These scans can be used to locate the specific areas inside the lungs that can be

cancerous. Research has shown that people at higher danger of lung cancers and screened

with CT scans were saved at large, when compared to chest x-rays. For the people having

higher risk of getting cancer may be screened yearly with CT or MRI scans. So that before the

symptoms starts and it will help them in decreasing the risk of dying from lung cancer.

Presently, Image processing methods are extensively used in a number of medical are-as.

Since the early diagnosis of cancer can help in saving the life, Image processing methods are

being developed in locating the cancerous tissues for treatment in the lungs, breast, and

pancreas and so on. Image quality is very much important, which is obtained through X-Ray,

CT and MRI Scans. The accuracy in locating the cancerous tumors may be obtained through

Image processing methods such as image segmentation.

3. METHODOLOGY

Lung cancers are found to be the most risky and widespread cancer in the world which cause

more deaths. So there is a need for the early detection of the disease. Early detection can save

the people from death by giving treatment at the early stage itself.

The work is divided in to two stages 1. Image Filtering stage: Even though the images of

the present age are more clear, in order to make the image better and accurate, image filtering

is done to keep the image from noise, corruption or interference free. The Mean and median

filters are used for filtering the images from noise. 2. Image Segmentation stage: In order to

locate the cancerous issues in the lungs, a method called image segmentation is performed.

Segmentation is a method of partitioning an image into regions which are greater

meaningful for a specific cause. It is one of the steps to investigate and explain the image

[25]. In the field of medicine, segmented images are often used to make it easy in analyzing

the size, shape and borders of the selected organ of the patient. But, the process of image

segmentation is not so easy as we think. The problems such as highlights, shadows,

transparency, and item occlusion [26] are also to be considered during the segmentation

process. Two different methods are used for segmenting the images in this research, they are

Otsu‟s Thresholding approach and K-Means Clustering Segmentation approach.

Detection of Lung Cancer using Image Segmentation

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The Otsu‟s Thresholding algorithm is based on a single intensity threshold .This threshold

separate pixels into background and foreground pixels. The threshold is determined by

minimizing the intra-class intensity variance and by maximizing the inter-class variance. In k-

means clustering, the objects are divided into several clusters mentioned by the number „K.‟

Here, the features or characteristics are compared, and all objects having similar

characteristics are clustered together.

The lung is a vital organ that has to be monitored often. For monitoring, the lungs Images

may be obtained through any one of the imaging methods discussed. Then by using any one

of the segmentation algorithms discussed, the cancerous tissues if any may be identified and

treat-ed. The accuracy of segmentation methods plays an important role in identifying the

lung disorders [27].

For evaluating the methods used for segmentation, some parameters of the processed

images are calculated. Some of parameters used for evaluating the image processing

techniques are signal to noise ratio (SNR), Peak signal to noise ratio (PSNR), timing run,

histograms, Mean Square Errors (MSE), specificity, sensitivity, accuracy and so on. In this

research the evaluation parameters considered are MSE [28], SNR [29] and PSNR[30]. The

parameters of MSE, SNR and PSNR are evaluated using the equations as follows

∑ ∑ ) )

(1)

∑ ∑ )

∑ ∑ ) )

(2)

(3)

Where, p(i, j) = the original image

q(i, j)=the segmented output image

MxN= the number of rows and columns in the images

4. RESULTS AND DISCUSSIONS

The original images of X-RAY, CT and MRI of the abnormal lungs with tumour after the pre-

processing are shown in Fig2a, Fig 3a, Fig. 4a respectively. Fig.2, Fig.3 and Fig.4 shows the

segmentation of images using Otsu‟s segmentation algorithm. This method first converts the

original colour image in to grayscale image and then works on it .The grayscale images of the

lung with tumour are shown in Fig 2b, Fig3b and Fig4b respectively. The histograms of the

grayscale images used for variance calculation are shown in Fig.2c, Fig.3c and Fig. 4c.Finally

the segmented images using Otsu‟s segmentation algorithm is shown in Fig.2d, Fig.3d and

Fig.4d.

(a) Original X-Ray Image (b) Original Gray Scale Image

V. Kannan and V. Jagan Naveen

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(c) Histogram (d) Segmented Image

Figure 2 Otsu Segmentation of X-Ray Image

(a) Original CT Image (b) Original Gray Scale Image

(c) Histogram (d) Segmented Image

Figure 3 Otsu Segmentation of CT Image

(a) Original MRI Image (b) Original Gray Scale Image

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(c) Histogram (d) Segmented Image

Figure 4 Otsu Segmentation of MRI Image

(a) Original X-Ray Image (c) Segmented Image

Figure 5 K-Means Segmentation of X-Ray Image

(a) Original CT Image (c) Segmented Image

Figure 6 K-Means Segmentation of CT Image

(a) Original MRI Image (c) Segmented Image

Figure 7 K-Means Segmentation of MRI Image

V. Kannan and V. Jagan Naveen

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Fig. 5, Fig. 6 and Fig. 7 shows the segmentation of images using K-Means Clustering

algorithm. The segmented images using K-Means Clustering algorithm are shown in Fig. 5b,

Fig.6b and Fig.7b respectively.

It is found that by viewing the image itself, comparing the two image segmentation

algorithms used in this research, K-Means Clustering algorithm shows a better result in

segmenting the lung tumor. Also Otsu‟s segmentation algorithm has segmented to a certain

extent on the CT and MRI images as shown in Fig2d and Fig3d and its performance is poor

on X-Ray image as shown in Fig4d.

The performance of the algorithms used are also evaluated by calculating the MSE, SNR

and PSNR on the segmented images obtained from the two different methods.Table1

andTable2 shows the values of evaluation parameters for the images from the methods.

Table 1 Otsu Segmentation of Images

Image Type MSE SNR PSNR

X-Ray Image 7154.94 5.39 9.60

CT Image 9464.61 4.74 8.37

MRI Image 12704.75 4.37 7.09

Table 2 K-Means Segmentation of Images

Image Type MSE SNR PSNR

X-Ray Image 5859.47 6.26 10.45

CT Image 18334.38 -0.53 5.50

MRI Image 17442.16 3.00 5.71

It is observed from the results of the segmented images obtained from both Otsu‟s

Thresholding and K-Means Clustering methods, better segmentation can be obtained using

K-Means Clustering .Also lung cancer disease can be detected at early stages using K-Means

Clustering algorithm and can increase the survival rate of the patients.

5. CONCLUSION

The image segmentation techniques which may be useful for earlier disease detection for

saving the precious human life is considered. Lung cancer is a disease widely spread on the

smokers. As an early screening X-Ray, CT and MRI images are used. This research also

concentrated on those images and included two image processing algorithms for image

segmentations .The segmentation algorithms are Otsu‟s segmentation Algorithm and

K-Means Clustering segmentation algorithm. It is found that by viewing the image itself and

by comparing the two image segmentation algorithms used, K-Means Clustering algorithm

shows a better result in segmenting the lung tumors irrespective of the type of images. Otsu‟s

segmentation algorithm has segmented to a certain extent on the CT and MRI images and its

performance is poor on X-Ray image.

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