A Review on the Abnormalities of Diabetic Retinal Images

A Review on the Abnormalities of Diabetic Retinal Images

E . Dhiravidachelvi

Research scholor,

Electronics and communication Engineering Sathyabama University

Chennai,Tamilnadu

Dr. V. Rajamani

professor

Electronics and Communication Engineering veltech-multi tech engineering college chennai, Tamil nadu.

Abstract: In recent biomedical field, ophthalmology has a significant role. In order to identify and detect the pathologies in diabetic retinopathy accurately, and correctly converge on time, it requires computer aided techniques. This paper focuses the various abnormalities of the retinal images and its procedure of the automated techniques involved in it. And also it provides performance analysis in terms of sensitivity and specificity calculations for the various techniques behind the micro aneurysms, exudates and hemorrhages.

Keywords: Diabetic retinopathy, abnormalities, micro aneurysms, exudates, hemorrhages

1. INTRODUCTION Diabetic Retinopathy (damage to retina)

The main cause of vision loss is the diabetic retinopathy and

its prevalence is set to continue rising. The early detection may be used to encourage improvement in diabetic control. When the small blood vessel in the retina has a high level of glucose, the vision will be blurred. Over a period of time the retina has some abnormalities like microanesysms, exudates and hemorrhages. For the diagnosis, ophthalmologists use color retinal images of a patient acquired from digital fundus camera. Prolonged diabetes causes micro vascular leakage and micro vascular blockage within the retinal blood vessels.

Fig1: retinal image

The literature on the automatic retinal image diagnosing algorithms are classified to the following steps

1. Preprocessing

2. Feature Extraction/segmentation

3. Classification

   2. LITERATURE

   1. EXUDATES:

One of the visible signs. These are extends into the macula area, vision loss can occur. The exudates can be classified as Hard, Soft Exudates; hard exudates (intra retinal lipid exudates) are yellow deposits of lipid and protein within the sensory retina. Soft exudates (cotton wool spots) they are white, fluffy lesions in the nerve fiber layer.

Fig2: Soft Exudates Hard Exudates

TABLE 1

Fig3: microaneurysns

TABLE II

B MICROANEURYSMS

The diabetes key lesion is microanesysms. These are the focal dilatations of retinal capillaries, the diameters of 10 to 100 microns and appear as red dots.

C HEMORRAGHES

When the wall of a capillary is weakened, it may rupture giving rise to an intra retinal hemorrhages. Usually it is round or oval (dot or blot). Dot hemorrhages appear as bright red dots and are same size as large MAs. Blot hemorrhages are larger lesions they are located within the mid retina and often within or surrounding areas of ischemia.

Fig4: hemorrhages

TABLE III

D. PERFORMANCE ANALYSIS

120

100

80

p>60

40

20

0

Fig5: Exudate analysis

Snsitivity specificity

Akarasophra

Dr.kekra(mo

Akara Ivosores Nanyang Diptoneel

Alireza Atulkumar Mariagarcia

kittipol Hussain

–

Sensitivity

specificity

120

100

80

60

40

20

0

–

Fig6.Microaneurysms Analysis

120

100

80

60

40

20

0

Sensitivity

Specificity

Fig7: hemorrhages

E .CONCLUSION

This Paper will give the idea about the Automatic analysis of Diabetic retinopathy which affects the vision. From this, the new authors can get the understanding about the Automatic Screening and detection of various lesions at the early stage,

and it will give the preventive measures to the blindness. The summary will give the performance analysis of the authors of various Universities also.

REFERENCES

EXUDATES

1. Akara Sopharak,bunyarit uyyanonvara,Automatic Exudates detection from Diabetic Retinopathy Retinal Image using Fuzzy c means and morphological methods,3rd International conference on Advances in computer science and technology,2007,359-364.

2. Dr. H. B. Kekre, Dr. Tanuja K. Sarode, Ms. Tarannum Parkar , Hybrid Approach for Detection of Hard Exudates, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No. 3, 2013

3. Anitha Somasundaram, and Janardhana Prabhu,Detection of Exudates for the Diagnosis of Diabetic Retinopathy, International Journal of Innovation and Applied Studies ,Vol. 3 No. 1 May 2013, pp. 116-120.

4. Mehdi ghafourian fakhar eadgahi, Hamidreza pourreza, Localization of Hard Exudates in Retinal Fundus Image by Mathematical Morphology Operations 2012 2nd International conference on Computer and Knowledge Engineering (ICCKE), October 18-19, 2012, 978-1-4673-4476

5. M.PonniBala*, S.Mohanapriya, Dr.S Vijayachitra.,Detection of Exudates on Diabetic Retinopathy images Based on Morphological Operation and Connected Component Analysis , International Journal of Advanced Engineering Research and Studies IJAERS/Vol. I/ Issue II/January-March, 2012/86-88.

6. Akara Sopharak,bunyarit Uyyanonvara,Fine Exudates Detection Using Morphological Reconstruction Enhancement, Journal of Applied Biomedical,volume1,No 1,2010

7. Ivo Soares,Miguel Castelo Brance,Exudates Dynamic Detection in Retinal Fundus Images based on the Noise Map Ditribution,19th European signal Processing Conference,Spain,2011,page 46-50.

8. G.Ferdic Mashak Ponnaiah, Capt.Dr.S.Santhosh Baboo, Automatic optic disc detection and removal of false exudates for improving Retinopathy Classification Accuracy, International Journal of Scientific and Research Publications, Volume 3, Issue 3, March 2013

9. Nan Yang, Hu Chuan Lu ,An Effective Framework for Automatic Segmentation of Hard Exudates in Fundus images, Journal of circuits, Systems and Computers Vol 2,No 1,2013

10. Diptoneel Kayal, Sreeparna Banerjee,Detection of hard exudates using Simulated Annealing Based Thresholding mechanism in Digital Fundus Image, Journal of computer science and Information Technology, CSCP-2013,pp 119-124.

11. Sidra Rashid and Shagufta,Computerised Exudate Detection in Fundus Images Using Statistical Feature Based Fuzzy C mean Clustering, International journal of Computing and Digital System No 3,135-145,2013

12. Alireza Osareh,majid Mirmehdi,Comparative Exudate Classification using Support Vector Machines and Neural Networks, Journal of Medical Image Computing,springer-verlag 2002,pp413-420

13. Atul Kumar,Manish Srivastava,A.K sinha,A Segment Based Technique for Detecting Exudate From Retinal Fundus Image, International Journal of Computer science and engineering Technology,vol 3, No 7,2012

14. Maria Garcia,clara I.Sanchez,Neural network Based detection of Hard Exudates in Retinal Images, An international journal of computing

    Methodology and Software systems in Biomedical Practice,ELSEVIER,2009,vol 93,page 9-19.

15. Kittipol Wisaing ,Nualsawat ,Automatic Detection of Exudates in diabetic retinopathy images, Journal of Computer Science 8980,1304- 1313,2012

16. Hussain F.Jaafer,Asoke K.Nandi ,Automated Detection Of Exudates in Retinal Images Using a Spilt And- Merge Algorithm,18th European Signal Processing conference 2010,page 1622-1626.

MICROANEURYSM

1. A.Sopharak, B.Uyyanonvara and S.baraman,Automatic micro aneurysm Quantification for Diabetic Retinopathy Screening, world Academy of Science, engineering and Technology 2013,page 1735- 1738

2. C.I.O.Martins ,R.M.S.veras,G.L.B.Ramalho,Automatic Microaneursysm Detection and Characterization through Digital Color Fundus images, International Joint Conference-Brazilian Symposium on Artificial Intelligence and Brazilian symposium on Neural Networks,2010

3. J.praKash, K.Sumathi,detection and Classification of Microaneursysm for Diabetic retinopathy, International journal of Engineering research and Applications, 2013,page 31-36

4. M.usman Akram, Shehzad Khalid, Shoab A.Khan,Identification and classification of micro aneurysms for Early detection of diabetic retinopathy, Pattern Recognition,ELSEVIER,2012

5. K. Adal, S. Ali, D. Sidib, Automated Detection of Micro aneurysms Using Robust Blob Descriptors, SPIE Medical Imaging – Computer- Aided Diagnosis, Orlando – FL : United States (2013).

6. A.Shaeidi,An Algorithm for Identification of Retinal Micrianeurysms,Journal of Serbian society for Computational Mechanics ,vol 4,No1,2010,pp 43-51

7. Sekineh Asadi Amiri, Hamid Hassan pour, Detection of Micro aneurysms in Retinal Angiography Image using the circular Hough Transform, Journal of Advances in computer Research ,vol 3,No 1,2012,pages 1-12

8. Sujith Kumar S.B, Vipula Singh ,Automatic Detection of Diabetic Retinopathy in Dilated RGB Retinal Fundus Images, international journal of computer Applications ,volume 47,No.9,2012

9. Atsushi Mizutani, Chisako Muramatsu,Automated Microaneursysm Detection Method based on Double Ring Filter in Retinal Fundus Images, medical Imaging 2009 proceedings of SPIE vol 7260,IN-1

10. A.Alaimahal,Dr.S.Vasuki,Identification of Diabetic Retinopathy Stages in Human Retinal Images, International journal of Advanced Research on Computer Engineering and Technology ,Volume 2, issue 2,2013

11. Akara Sopharak, Bunyarit uyyanonvara,Automatic Microaneursysm Detection From Non Dilated Diabetic retinopathy retinal Images, proceedings of the world congress on engineering 2011,vol II ,page 6-8

12. G.Yang, L.Gagnon, S.Wang,Algorithm For Detecting Micro aneurysms in Low Resolution Color Retinal images,2001

13. Lee Streeter and Michael J.Cree,Microaneurysm Detection in Color Fundus Images, image and Vision Computing NZ, 2003,page 280-283

14. R.Gowtham,Automatic Identification and Classification of Micro aneurysms for Detection of Diabetic Retinopathy, International journal of Research in Engineering and technology, 2014,vol 03,issue 02

15. Md.Muhid Ahmed, Dr.K.Kumaravel,Internal Components Combination to Detect Microaneurysm, IJAIR,2013,vol 2,issue 5, page 155-158

16. Murugan.R, Dr. Reeba Koreh, Microaneurysms Detection Methods in Retinal Images Mathematical Morphology , International journal of Advances in Engineering science and technology, 2003

HEMORRHAGES

1. Giri Babu Kande, T. Satya Savithri et al, Automatic detection of microanuresysms and the Hemorrhages in digital fundus Images, Journal of Digital Imaging 2010, 23(4), 430 437.

2. Sergio Bortolin Junior and Danner Welfer, Automatic detection of microanuresysms and the Hemorrhages in color eye fundus images, International Journal of Computer Science and Information Technology,Vol 5, No 5, 2013.

3. Athira R.V. Ferlin Deva Shahila D, Detection of retinal Hemorrhages using splat feature classification techniques, Journal of Engineering Research and Applications, Vol 4, Issue 1 (version 3), 2014, pp. 327 330.

4. Yuji Hatanaka, Toshiaki Nakagawa, Improvement of automatic hemorrhage detection methods using brightness correction of fundus images, Journal of Medical Imaging, 2088, Vol 6915.

5. L. Tang M. Niemeijer, J.M. Reinhasdt et al, Splat feature classification with application to Retinal Hemorrhage Detection in Fundus images, IEEE Transactions, Medical imaging, 2012.

6. V. Vijayakumari, Detection of Hemorrhages in retinal images, Indian Journal of Applied Research, Vol 3, Issue 7, 2013.

7. S.A. Barman, C. Sinthanayothin, Classification of Hemorrhages pathologies on digital fundus images using a combination of neural network and tracking algorithms.

8. Nidhal Khdhair EI Abbadi et al, Improvement of Automatic Hemorrhages Detection methods using shapes recognition, Journal of Computing and Applications.

9. Tareq AI Saeed, Doaa Youssef et al, Automatic detection of Microaneursysm and Hemorrhage for screening of retinal diseases, 3rd International Conference on Intelligent Computational systems, 2013, 39 43.

10. Deepa D, Sumathi P, A survey on usage of Data Mining Techniques in the Detection of Hemorrhages in Fundus Images, International Journal of Advanced Research in Computer Science and Software Engineering, Vol 3, Issue 10, 2013.

11. Alan D. Fleming, Keith A. Goatman et al, The role of Hemorrhages and exudates detection in automated grading of diabetic retinopathy, Br. Journal of Opthalmol, 2012,706 711.

BIOGRAPHIES

E.Dhiravida selvi, received B.E in Electronics and Communication Engineering from The Indian engineering college, Manonmani Sundaranar University, tirunelvelli, Tamilnadu, India,in the year1996, Post graduate degree in M.E

Communication system from Thiyagarajar College of engineering Madurai, Tamilnadu, India in the year of 1998 and Pursing Ph.D at SathyaBama University with a specialization in Medical Image Processing. She started her academic carrier in the year 1999 as Lecturer. Currently, she is working as a Hod in the Mohamed Sathak A.J college of engineering ,Chennai,tamilnadu,India. He is the life member of IETE,ISTE, New Delhi, India.

V.Rajamani, received B.E in Electronics and Communication Engineering from national Engineering College,Madurai Post graduate degree in M.E. Applied Electronics from Govt. College of Technology, degree from the Institute of Technology, Banaras

Hindu University, Varanasi, Uttar Pradesh, India in 1999 with a specialization in semiconductor device modeling for optical communication receivers.. Currently, he is working as a Principal in the IndraGanesan College of Engineering, Tiruchirappalli, Tamilnadu, India. He has published more than 130 papers in the referred national and international journals and conference proceedings. Under his guidance, 10 research scholars have completed their doctoral degrees. He has also completed 10 PG dissertations also. His area of interest includes Device Modeling, VLSI Design, Image Processing and Optical Networking and Communication. He is the life member of ISTE, New Delhi, India and member in IAENG.