This document presents an algorithm to automatically detect glaucoma from ultrasound images of the eye. Glaucoma occurs when fluid pressure inside the eye increases, damaging the optic nerve. Current detection methods like tonometry and ophthalmoscopy are manual and inaccurate. The proposed algorithm first enhances low-resolution ultrasound images using contrast improvement and speckle noise reduction. It then locates the anterior chamber and calculates the angle between the iris and cornea, which is used to diagnose glaucoma. Testing on sample images found the algorithm identified clinical parameters accurately in 97% of cases, outperforming manual analysis. This automatic detection method could improve efficiency and accuracy of glaucoma screening.

1. K.Chiranjeevi et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES
Vol No. 6, Issue No. 1, 077 - 080
Automatic Detection of Glaucoma Disease In Eye
K.Chiranjeevi Prabhakar Telagarapu
Dept.of. ECE Dept.of. ECE
GMR Institute of Technology GMR Institute of Technology
Rajam,Srikakulam Dist,AP,India Rajam,Srikakulam Dist,AP,India
Chiru404@gmail.com Prabhakart2@gmail.com
Abstract— Glaucoma arises due to the inadequate fluid group of diseases of the optic nerve involving loss of retinal
flow from the drainage canals of the eye, leading to the ganglion cells in a characteristic pattern of optic neuropathy.
crystallization of the fluid in the cornea and iris regions. Eye has pressure just like blood, and when this intraocular
Especially in closed angled Glaucoma, fluid pressure in the eye pressure (IOP) increases to dangerous levels, it damages the
increases because of inadequate fluid flow between the iris and optic nerve. This can result in decreased peripheral vision and,
the cornea. One important technique to assess patients at risk of eventually, blindness. Glaucoma is similar to ocular
Glaucoma is to analyze ultrasound images of the eye to detect the hypertension but with accompanying optic nerve damage and
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structural changes. Currently, these images are analyzed vision loss. Although raised intraocular pressure is a
manually. In this paper, an algorithm is proposed to significant risk factor for developing Glaucoma, there is no set
automatically compute this accretion from the ultrasound images threshold for intraocular pressure that causes Glaucoma. One
of the eye. Apart from improving the contrast of the low person may develop nerve damage at a relatively low pressure,
resolution ultrasound image, the algorithm aims to determine the
while another person may have high eye pressures for years
exact location of the apex point of the anterior chamber region
for efficient angle calculation. It is highly imperative to detect
and yet never develop damage. Untreated Glaucoma leads to
permanent damage of the optic nerve and resultant visual field
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Glaucoma in its early stages for diagnosis and hence the
algorithm also addresses the importance of precise results with
effective immunity towards speckle noise. This work shows a
technique to improve the efficiency of clinical interpretation of
loss, which can progress to blindness. In this paper, the Closed
Angle Glaucoma is addressed, in which the fluid at the front
of the eye cannot reach the angle and leave the eye. The angle
gets blocked by part of the iris. People with this type of
Glaucoma in ultrasound images of the eye.
Glaucoma have a sudden increase in eye pressure. Symptoms
include severe pain and nausea, as well as redness of the eye
Keywords- Glaucoma, drainage canals, cornea, and iris region, and blurred vision. This status requires immediate medical
ultrasound images. attention.
I. INTRODUCTION II. CURRENT TECHNIQUES TO DETECT
GLAUCOMA
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Glaucoma is a group of diseases that can steal sight
without warning or symptoms. Some of the alarming facts
about Glaucoma are (1) Glaucoma is a leading cause of Regular Glaucoma check-ups include two routine eye
blindness, (2) There is no cure for Glaucoma yet, (3) Everyone tests: Tonometry and Ophthalmoscopy.
is at risk and (4) There may be no symptoms. Nearly half of
those with Glaucoma do not know they have the disease. This 2.1 Tonometry
has been shown repeatedly in studies conducted in developed The Tonometry test measures the inner pressure of
countries. Glaucoma is a potentially blinding disease that
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the eye. Usually drops are used to numb the eye. Then the
affects 66 million persons worldwide. It is the second leading doctor or technician will use a special device, called
cause of blindness worldwide. The disease is characterized by Tonometer, which measures the eye’s pressure. The normal
typical changes in the optic nerve (the nerve that connects the range of this pressure is in between 10mmHg and 22mmHG.
eye to the brain) with associated visual field defects (the area
seen by the eye). Since the outer portion of the visual field is 2.2 Ophthalmoscopy
the first to be affected and most types of Glaucoma are Ophthalmoscopy is used to examine the inside of the
asymptomatic the disease is often diagnosed once significant eye, especially the optic nerve. In a darkened room, the doctor
vision/field has been lost. Therefore, early diagnosis is will magnify the eye by using an ophthalmoscope (an
essential so that treatment to halt/slow progression can be instrument with a small light on the end). This helps the doctor
instituted. Glaucoma study from Chennai city and rural look at the shape and color of the optic nerve.If the pressure in
Tamilnadu reveals that every 1 on 3 patients above 40 years the eye is not in the normal range (10mmHg to 22mmHg), or
having vision related problems were diagnosed with if the optic nerve looks unusual, then one or two special
Glaucoma. When the Glaucoma is understood and managed, Glaucoma tests will be done. These two tests are called
humans can continue to live their life fully. Glaucoma is a Perimetry and Gonioscopy.
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2. K.Chiranjeevi et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES
Vol No. 6, Issue No. 1, 077 - 080
2.2.1 Perimetry based algorithms without compromising on the speed,
accuracy, sensitivity, cost and compatibility of the product.
The Perimetry test is also called a visual field test. Ultrasound images of eye are usually associated with poor
During this test, the patient will be asked to look straight
resolution, poor contrast, noise and divaricated anterior
ahead and then indicate when a moving light passes his/her chamber edges. Algorithm is proposed to effectively mitigate
peripheral (or side) vision. This helps draw a ― map‖ of
the above challenges.
patient’s vision.
2.2.2 Gonioscopy III. ALGORITHM DESIGN
Gonioscopy is a painless eye test that checks if the This algorithm describes a new method to detect
angle where the iris meets the cornea is open or closed, features in ultrasound images, which shows good performance
showing if either open angle or closed angle Glaucoma is in detection of difficult features. The developed techniques
present. make use of major image processing methods and
fundamentals. In order to calculate the clinical parameters of
interest, new region classification and segmentation
techniques are developed as well as other signal processing
techniques are used to locate the scleral spur. The ultrasound
images of the eye are very noisy, with poor resolution and
weak edge delineation, which required the development of a
three-step method to overcome these challenges. The complete
algorithm is shown in Figure 3.1.
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Figure 2.1 Clinical parameters in Gonioscopic images
2.3 Manual Calculation of AOD from Ultrasound Images of
the Eye
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In this method, the doctor examines the Ultrasound
IV. RESULTS
image of the patient’s eye and he/she estimates the angle
between the iris and the cornea. If the estimated angle is less The angles between iris and cornea for Ultrasound images of
than 190, then the eye is treated as Glaucoma affected, different patients are calculated and decision about the
otherwise as normal eye. But the manual estimation may be presence of Glaucoma is made follows.
wrong. 4.1 Results for Ultrasound Image 1
2.4 Disadvantages of Current Techniques
Manual analysis of eye images is fairly time
consuming, and the accuracy of parameter measurements
varies between experts. For this reason, an algorithm is
developed to automatically analyze eye ultrasound images.
The proposed algorithm is expected to reduce the processing
time taken by the existing techniques of manual/computer- Figure 4.1: Input Ultrasound Image 1
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3. K.Chiranjeevi et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES
Vol No. 6, Issue No. 1, 077 - 080
TABLE :1 Comparison of Results with Current Techniques for Image 1 4.3 Results for Ultrasound Image 3
As the Intraocular Pressure is same as the threshold value, the
status of Glaucoma cannot be decided using Tonometry. As
the Perimetry method is the visual filed of the patient, in this
method also the status of Glaucoma cannot be decided. Even
though AOD is greater than 190 in the case of Gonioscopy and
direct view, which decided that Glaucoma is present, the
developed algorithm detected Glaucoma, as AOD is less than
190.
4.2 Results for Ultrasound Image 2
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Figure 4.3: Input Ultrasound Image 3
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In this case, all methods including developed algorithm
decided that Glaucoma is present. Perimetry method also
decided that Glaucoma is present, as the visual field of the
patient’s eye is very poor.
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4.4 Results for Ultrasound Image 4
Figure 4.2: Input Ultrasound Image 2
TABLE :2 Comparison of Results with Current Techniques for Image 1
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As the Perimetry method is the visual filed of the
patient, in this method also the status of Glaucoma cannot be
decided. Even though Tonometry and Gonioscopy decided
that Glaucoma is present, the developed algorithm detected no
Glaucoma, which prevents the unnecessary surgery.
Figure 4.3: Input Ultrasound Image 3
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4. K.Chiranjeevi et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIES
Vol No. 6, Issue No. 1, 077 - 080
TABLE :4 Comparison of Results with Current Techniques for Image 4 patient’s ultrasound image, leading hopefully to an increase in
efficiency and a reduction of cost.
ACKNOWLEDGMENT
The Authors wish to thank Guru Kamesh Reddy,
JTO,AP,India. For his sugessions which have the improved
the presentation of the material in this paper.
REFERENCES
[1] R. Youmaran, P. Dicorato, R. Munger, T.Hall, A. Adler -
Automatic Detection of Features in Ultrasound Images of the Eye,
In this case, all methods including developed IMTC 2005 – Instrumentation and Measurement Technology
algorithm decided that Glaucoma is present. Conference, Ottawa, Canada, 17-19 May 2005.
[2] Xiaoyang Song, Keou Song, Yazhu Chen - A Computer-based
In ultrasound imaging, speckle noise severely Diagnosis System for Early Glaucoma Screening, Proceedings of
degrades the visual quality of the image. In order to achieve the 2005 IEEE Engineering in Medicine and Biology 27th Annual
high accuracy when extracting features, speckle must be Conference Shanghai, China, September 1-4, 2005.
filtered without destroying any important characteristics in the [3] Rafael C. Gonzalez, Richard E. Woods, ― Digital Image
image. In the developed algorithm, speckle noise was reduced Processing‖, Second Edition, Pearson Education Asia Publications.
T
using a multi-scale algorithm. It is worthwhile to investigate a [4] Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins, ― Digital
different speckle reduction technique that do not depend on Image Processing using MATLAB®‖, Pearson Education Asia
the selection of the window size and that can be used on the Publications.
ultrasound images of the eye before edge enhancement. One [5] Glaucoma Research Foundation - funding innovative research to
find a cure for Glaucoma.251 Post Street, Suite 600, San
easy way to reduce speckle is to average multiple uncorrelated Francisco, CA.
images of the same object obtained from different spatial
positions. However, this procedure is computationally costly
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and will increase the processing time of the algorithm. It
seems to design an algorithm for fine enhancement, which
does not require the selection of a fixed window size and to
reduce speckle noise based on each pixel surrounding area.
K.Chiranjeevi received B.E Electronics and
Communication Engineering from
from JNTU Kakinada, He is working as Asst.
Professor in GMR Institute of Technology. His
J.N.T.U.
Anantapur, and M.Tech Instrumentation and Control
research interests are in Signal Processing and Image
However, for images with very poor resolution, more iteration Processing.
can be applied until all pixels lying in the same local
neighborhood have similar intensity values close to the initial
spike value. If this technique shows improvement in speckle
T.Prabhakar received M.Tech degree from Jawarlal
reduction and does not destroy edges in the original image, the
Nehru Technological University Kakinada, Andhra
enhancement process in the algorithm will require less Pradesh, India. B.Tech degree in Electronics and
iteration, resulting in a considerable reduction of the Communication Engineering from SIR C.R.Reddy
processing time.
A
College of Engineering, Eluru, Andhra Pradesh,
India. He is joined as Lecturer in the Department. Of
Electronics and Communication Engineering at
V. CONCLUSION GMR Institute of Technology, Rajam, Srikakulam
This thesis has developed an algorithm to District, Andhra Pradesh, India in 2002. Prior to join in this Institute he
worked as a Service Engineer in Machine Diagnostics and Deployed to work
automatically identify clinical features in ultrasound images of at National Remote Sensing agency, Department. Of. Space, Hyderabad for 1
the eye. The algorithm computes the AOD 500 used to year 1 month and Trainee Programmer in Indo Tech Computers, for 8 months
measure the presence and severity of glaucoma. Overall, the in Hyderabad. He is presently working as Senior. Assistant Professor in the
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algorithm predictions are very advantageous compared to the Department. Of Electronics and Communication Engineering at GMR
technologist’s observation. In the processed images, features Institute of Technology. Having Total experience is 12 years out of which 10
years in Teaching (GMRIT) and 2 Years in Industry. His research interests are
were correctly identified in 97% of the cases. 3% of images Communication, Signal Processing and Image Processing. He has published
presented inaccurate approximation of the clinical parameters. 10 Technical papers in various International journals and conferences. He is a
The difficulties encountered in measuring clinical parameters, life member of ISTE Since 2002.
which are associated with the speckle noise, poor contrast,
poor resolution, and weak edge delineation present in the
processed ultrasound images, are accurately eliminated.
However, the designed algorithm failed for a few of images,
where more noise is present. The algorithm was designed with
a goal of robustness through the use of enhancement process
on the original image, and by validation of the proper
segmentation of the anterior chamber at each step. Overall, the
benefit of this work is the ability of algorithm to reduce the
processing time and improve processing consistency for each
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