Automatic coronary artery detection in cardiogram image

Automatic Coronary Artery Detection in Cardiogram Image

Esmael Ali Ramadan Hamuda

A dissertation submitted in partial fulfillment

of the requirement for the award of degree

of Master of Engineering

(Electrical-Electronics & Telecommunication

)

Faculty of Electrical Engineering

Universiti Techonologi of Malaysia

ABSTRACT

The Myocardium Infarction or generally known as MI, is the most dangerous

and serious disease that effects the health of the human heart. MI usually attacks

and damages the heart muscle by blocking the path of coronary artery.

Echocardiography is a widely used imaging technique to examine myocardial

function in patients with known or suspected heart disease. In clinical practice, the

analysis mainly relies on visual inspection or manual measurements by experienced

cardiologists. For researchers, the analysis of myocardium can be done with tissue

samples taken from very small areas of interest manually. However, this manual

process is tedious and time-consuming, and is vulnerable to error due to human

weaknesses. Therefore, this project is aimed to automatically detect the wall of the

coronary artery that separates the left and right chambers of the myocardium, so that

it becomes much easier to analyze this particular area. In order to achieve this aim,

a number of per-processing methods have been applied on the real medical image of

the heart from the echocardiography which is performed in an offline manner.

These pre-processing operations involved the use of binarizing, down sampling,

median filtering, morphological erosion, morphological dilation, logical AND

operation and morphological connected component labeling. The classification of

the coronary artery area was done based on two features extraction. One is the

height to width ratio and another is the label to image area ratio. The performance

vi

ABSTRAK

Myocardium Infraction atau pun lebih dikenali sebagai MI adalah salah satu

penyakit jantung berbahaya yang dihidapi oleh manusia. MI umumnya menyerang

dan merosakkan otot jantung dengan menutup laluan ke arteri koronari.

Echocardiography ialah satu teknik memproses imej yang digunakan secara meluas

untuk menguji fungsi myocardial seseorang pesakit yang dicurigai mempunyai sakit

jantung. Kebiasaannya, analisis dilakukan secara visual dan pengukuran dilakukan

secara manual oleh pakar kardiologi yang berpengalaman. Bagi para penyelidik

pula, analisis myocardium boleh dilakukan dengan mengambil sampel tisu dari

kawasan kecil yang berkenaan. Walaubagaimanapun, operasi manual ini adalah

menyusahkan dan membuang masa, dan terdedah kepada kesilapan disebabkan

kelemahan manusia. Oleh itu, projek ini adalah bertujuan untuk mencari dinding

koronari arteri yang membezakan ruang kanan dan kiri jantung secara automatik,

bagi menyenangkan analisis di kawasan ini. Untuk mencapai objektif ini, berberapa

operasi pra-pemprosesan secara offline dilakukan ke atas imej medikal yang asal,

iaitu imej yang diperolehi daripada echocardiography. Operasi pra-pemprosesan

yang dilakukan antaranya ialah operasi binari, down sampling, penapisan penengah,

operasi morphology erosion, morphology dilation, operasi logik DAN dan operasi

morphology connected component labeling. Dalam projek ini, proses klasifikasi ke

atas arteri koronari telah dilakukan berdasarkan dua ciri pilihan. Ciri pertama adalah

nisbah antara tinggi dan lebar manakala ciri yang kedua adalah nisbah antara luas

label terhadap luas imej. Projek ini didapati mempunyai ketepatan sebanyak 90%

TABLE OF CONTENTES

CHAPTER TITEL PAGE

DECLARACTION ii

DEDICATION iii

ACKNOWLEDGMENT iv

ABSTRACT v

ABSTRAK vi

TABEL OF CONTENTS vii

GLOSSARY OF TABELS x

GLOSSARY OF FIGURES xi

LIST OF NOTATIONS xiv

LIST OF ABBREVIATIONS xv

LIST OF APPENDICES xvi

1 INTRODUCTION 1.1 Introduction 1

1.2 Basic Heart Anatomy 2

1.3 Myocardial Infarction (Heart Attack) 4

1.3.1 Understanding the heart and coronary arteries 5

1.3.2 What happens when someone has a myocardial infarction ? 6

1.4 Ultrasound imaging 6

1.4.1 Introduction 6

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1.6 Scope of Work 7

1.7 Problem statement 8

1.8 Project outline 8

2 Literature Review 2.1 Introduction 10

2.2 Texture analysis 10

2.2.1 The methods are used to analyse the texture. 11

2.3 Myocardial Motion and Deformation Analysis 12

2.3.1 Introduction 12

2.3.2 Cardiac Motion Patterns 13

2.3.2.1 The methods are used to analyses the myocardium motion 14

2.4 Conclusion from previous studies 16

3 Methodology 3.1 Introduction 17

3.2 System overview 17

3.3 Preprocessing 18

3.3.1 Binary image 19

3.3.2 Down Sample 20

3.3.3 Median Filter 20

3.3.4 Morphological operation 22

3.3.4.1 Introduction 22

3.3.4.2 Erosion 23

3.3.4.3 Dilation 24

3.3.4.4 Logical ‘AND’ Operation. 26

3.3.4.5 Connected-Component Labeling 27

3.3.4.5.1 Introduction 27

3.3.4.5.2 The concept of pixel connectivity 28

3.3.4.5.3 How the connected

component labeling

works? 29

3.4 Feature Extraction 31

3.4.1 Ratio of label area to image area (R1) : 31

3.4.2 Height to Width ratio (R2): 33

3.5 Classification and detection 34

4 Experiment & Results 4.1 Introduction 37

4.2 Preprocessing Results 37

4.2.1 Binary Image Results 37

4.2.2 Median Filter Results 38

4.2 3 Erosion Results 40

4.2 4 Dilation Results 41

4.2.5 Logical AND Operation Results 42

4.2.6 Connected Component Labeling Results. 43

4.3 Feature Extracted Results 45

4.3.1 Ratio of Label Area to Image Area(R1) Results 45

4.3.2 Height to Width Ratio (R2) Results 48

4.4 Testing results 52

4.5 Recognition Accuracy 54

4.6 Factors that Contribute to Low Accuracy 55

4.6.1 Class Coronary Artery Failure. 55

5 CONCLUSION & SUMMARY 5.1 Summary 58

5.2 Conclusion 58

x

References 60

Appendix A 65

Appendix B 70

GLOSSARY OF TABLES

TABLE NO TITEL PAGE

3.1 Truth-tables for AND operation. 27

4.1 The training results from measuring the ratio of label area to imageareafor15samples. 45

4.2 The training results from measuring of height to width ratio for each label that appears in 15 samples. 48

4.3 Table of combining the two features ratio. 51

4.4 Testing results for 10 samples. 53

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GLOSSARY OF FIGURES

FIGURE NO TITEL PAGE

1.1 (a) External View. 3

1.1 (b) Internal View. 4

1.2 Coronary artery got blocked. 5

1.3 (a) Ultrasound machine. 7

1.3 (b) Echocardiography image, atypical ultrasound image of human heart. 7

2.1 Atypical ultrasound image of human heart. 11

2.2 Basic motion patterns of contracting ventricle. The myocardium moves inwards (a) and thickens significantly (b) to maximize pumping efficiency. 13

3.1 Overall system architecture block diagram. 18

3.2 .Median Filter. 21

3.3 (a) structure ‘B’ (b) a simple binary image ’A’(c)Result of erosion process. 24

3.4 (a) Structure element ‘B’ (b)a simple binary image ‘A’ (c) Effect of dilation using structuring element. 25

3.5 Two types of neighbor hood pixel relationship. 28

3.6 Simple example for applying the connected component on binary image. 30

3.7 feature extraction (R1) for ratio label area to image area. 32

3.8 Feature extraction (R2) for height to width ratio. 34

3.9 The flowchart of the whole system. 36

4.1 The converted binary image for different samples .a, b, and c. 38

4.2 The resulting images after applying median filter for different samples ,a, b, and c. 39

4.4 TheDilation operator results for different samples a, b, and c. 42

4.5: Logical AND operation for different samples ,a, b, and c. 43

4.6 The results from applying the connecting component labeling for

different samples a, b, and c. 44

4.7 The plotting results of training samples(15) to find the range of ratio

of coronary artery area to image area. 47

4.8 The plotting results of training samples(15) to find the range of ratio of

height to width of coronary artery. 50

4.9 The range of ratio of the wall of coronary artery area to image area. 51

4.10 The range of height to width ratio of wall coronary artery. 52

4.11 The results of testing samples; the red region is a coronary

artery region which is detected automatically. 54

4.12 Plot of testing samples (10) to show which sample is out of range

(the range that has been made from training term). 56

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LIST OF NOTATIONS

F(x, y) Grayscale Image.

G(x, y) Binary Image.

H(x, y) Resized Image.

E(A,B) Eroded Operation

D(A,B) Dilated Operation.

) (

4 p

N 4 Neighborhood pixel relationship.

) (

8 p

LIST OF ABREVIATIONS

MI Myocardium Infarction .

R1 Ratio of Label Area to Image Area.

R2 Height to Width Ratio.

V Intensity Value.

B Structuring Element.

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LIST OF APPENDICES

APPENDIX TITLE PAGE

A Matlab Declaration. 65

B Some other Results. 70

CHAPTER 1

INTRODUCTION

1.1 Introduction

The heart is the most active organ in the human body. Beating about every

second throughout our lifetime, it continuously supplies the body with vital blood.

The heart has always played a key role in medical science and has even become a

major symbol for life. Its life-sustaining pumping function is realized by its powerful

muscular structure the so-called myocardium. Its activity is kept up by an efficient

circulatory system of coronary arteries that supplies the muscle with the essential

oxygen and nutrients. Silent but progressive occlusion and hardening of the coronary

arteries is the main cause for cardiac malfunction. It is caused by a build-up of fatty

deposits in the lining of the artery walls a process known as atherosclerosis. The lack

of blood supply the so-called ischemia reduces the heart’s ability to contract

normally. When one or more of the coronary arteries get completely occluded, blood

to the heart muscle is cut off and the affected myocardial segments get seriously

damaged or even die. This so-called myocardial infarction, also known as “heart

attack”, often occurs suddenly and may be life-threatening. Coronary artery disease

specifically, heart attack is the main cause of long-term disability and death

throughout the industrial world. In Europe, about four million people die of

cardiovascular disease every year, which is claiming more lives than the next five

leading causes of death altogether.

The heart is a restless working muscle that provides blood circulation to the

2

100 000 times per day and 30 to 42 million times per year. This corresponds to a

daily pumping capacity of about 7200 liters and 2.5 million liters per year. This

enormous activity is due to the heart’s highly optimized structure and functioning.

To be able to understand the origin and symptoms of MI, the heart’s basic anatomy

and its associated terminology is reviewed in Section 1.2.

Several heart diseases affect the heart muscle and reduce its ability to

contract normally The resulting loss in pumping efficiency leads to an undersupply

of the vital oxygen to the body, which may seriously harm other organs. The most

frequent. source for impaired wall motion is a process called atherosclerosis, which,

in its worst case, may lead to a life threatening heart attack. The heart attack disease

and its impact to cardiac function is summarized in Section 1.3.

In clinical routine, myocardial dysfunction can be diagnosed by a number of

tools including physical examinations, electrocardiograms, blood tests, and, in

particular, medical imaging techniques such as echocardiography (ultrasound image

);The ultrasound imaging is summarized in Section 1.4

1.2 Basic Heart Anatomy

The heart is a muscular organ that is located between the lungs in the middle

of the chest, behind and slightly to the left of the breastbone (sternum). It is

surrounded by a double-layered membrane that is called the pericardium. The heart

has four chambers as illustrated in Fig.1.1. The two upper chambers are called the

left and right atria, and the lower chambers are called the left and right ventricles.

The atria act as reservoirs for venous blood; they have a small pumping function to

assist ventricular filling. The ventricles are the major pumping chambers that deliver

blood to pulmonary (right ventricle) and systemic circulations (left ventricle). The

heart’s muscular walls are called myocardium. Its outer surface is called the

epicardium and its inner lining the endocardium. The wall that separates the left and

right atria and the left and right ventricles is called the septum. Four valves ensure

from one chamber to the upstream chamber (valvular regurgitation). The aortic and

pulmonic valves are referred to as the semilunar valves and are located at the

downstream sides of the left and right ventricle, respectively. The two

atrioventricular valves, the mitral and tricuspid valve, are located between the atria

and ventricles. The leaflets of the atrioventricular valves are connected to the

papillary muscles that are, inturn, connected to the walls of the ventricles. The

papillary muscles shorten during the contraction of the ventricles in order to prevent

a bulging of the atrioventricular valves towards the atria that would lead to

regurgitation. The anatomy of the human heart. anterior external view with coronary

arteries and veins shows in Figure 1.1.(a) and the internal view shows in Figure

1.1.(b).

Parts of external view:

1. Right Coronary (RCA)

2. Left Anterior Descending (LAD)

3. Left Circumflex (LCX)

4. Superior Vena Cava

5. Inferior Vena Cava

6. Aorta

7. Pulmonary Artery

8. Pulmonary Vein

4

Parts of internal view:

9. Right Atrium

10. Right Ventricle

11. Left Atrium

12. Left Ventricle

13. Papillary Muscles

14. Chordae Tendineae

15. Tricuspid Valve

16. Mitral Valve

17. Pulmonary Valve

1.3 Myocardial Infarction (Heart Attack)

Myocardial infarction (MI) means that part of the heart muscle suddenly

loses it's blood supply. Without prompt treatment, this can lead to damage to the

affected part of the heart. MI is sometimes called a heart attack or coronary

thrombosis.

1.3.1 Understanding the heart and coronary arteries

The heart is mainly made of special muscle. The heart muscle pumps blood

into arteries (blood vessels) which take the blood to every part of the body. Like any

other muscle, the heart muscle needs a good blood supply. The coronary arteries

take blood to the heart muscle. The main coronary arteries branch off from the aorta.

(The aorta is the large artery which takes oxygen-rich blood from the heart chambers

to the body.) The main coronary arteries divide into smaller branches which take

blood to all parts of the heart muscle. The following Figure shows how the blood

got blocked during his cycle through coronary artery .

6

1.3.2 What happens when someone has a myocardial infarction?

If someone has an MI, a coronary artery or one of it is smaller branches is

suddenly blocked. The part of the heart muscle supplied by this artery loses it's blood

(and oxygen) supply. This part of the heart muscle is then at risk of damage unless

the blockage is quickly undone. (Strictly speaking, 'infarction' means death of some

tissue due to a blocked artery which stops blood from getting past.)

If one of the main coronary arteries is blocked, a large part of the heart

muscle is affected. If a smaller branch artery is blocked, a smaller amount of heart

muscle is affected. In people who survive an MI, the part of the heart muscle which

dies ('infarcts') is replaced by scar tissue over the next few weeks.

1.4 Ultrasound Image

1.4.1 Introduction

Ultrasound imaging, also called ultrasound scanning or sonography, is a

method of obtaining images from inside the human body through the use of

high-frequency sound waves. The reflected sound wave echoes are recorded and

displayed as a real-time visual image. No ionizing radiation (x-ray) is involved in

ultrasound imaging. Obstetric ultrasound refers to the specialized use of sound

waves to visualize and thus determine the condition of a pregnant woman and her

embryo or fetus.

Ultrasound is a useful way of examining many of the body's internal organs,

including but not limited to the heart, liver, gallbladder, spleen, pancreas, kidneys

and bladder. Because ultrasound images are captured in real time, they can show

movement of internal tissues and organs and enable physicians to see blood flow and

heart valve functions. This can help to diagnose a variety of heart conditions and to

assess damage after a heart attack or other illness. The following Figures show the

.

1.5 Objectives

Thus, the main objective of this project is to automatically detect the wall of

the coronary artery that separates the left and right chambers of the heart , so that it

becomes much easier to analyze this particular area.

1.6 Scope of Work

This project involves the following specific steps.

1. Sources are from ultrasound images of the heart – echocardiogram.

2. Image will be processed using 8-bit gray scale.

3. Image size is fixed at 767 x 575 as given from the system.

4. Processing will be done in an off line system.

5. Processing tool will be MATLAB Software

8

1.7 Problem statement

1. In clinical practice, the analysis mainly relies on visual inspection or manual

measurements by experienced cardiologists.

2. For researchers, the analysis of the myocardium can be done with tissue samples

taken from very small areas of interest manually (using mouse to extract the

tissue samples from cardiogram image of the heart).

The manual methods are tedious and time-consuming, and visual assessment

leads to qualitative and subjective diagnoses that suffer from considerable inter- and

intra-observer variability. On the other hand, automatic detection method has the

advantage of being, less time consuming, robust and does not suffer inter- and

intra-observer variability.

1.8 Project outline

The project is organized into chapters. The outline is as following

Chapter 1-Introduction

This chapter discusses the objectives and scope of the project and gives a

general introduction on basic heart anatomy, MI, and ultrasound images.

Chapter 2- Literature Review

This chapter reviews the previous methods which have been worked on

myocardium image. Some of them have been related to texture analysis and the

Chapter 3-Methodolgy

This chapter presents the overall system methodology and discusses in details

each step that has to be take into consideration for classification purposes.

Chapter 4-Rsults .

This chapter shows the results for each process( preprocessing) has done on

the input image for this system and shows the result of the classification as well(

detecting the wall of coronary artery).

Chapter 5-Conclusion

This chapter consists of conclusion and suggestion for future improvement.