Detection of abnormalities in retinal images

Yamuna, T.; Maheswari, S.

doi:10.1109/ice-ccn.2013.6528500

Cited by 12 publications

(7 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unfortunately, many recognition systems only have a few samples from just the target class. For example, collecting images from the normal state of a retina is easier than collecting those from abnormal retinas [25].…”

Section: Introductionmentioning

confidence: 99%

One-class slab support vector machine

Fragoso

Scheirer

Hespanha

et al. 2016

2016 23rd International Conference on Pattern Recognition (ICPR)

View full text Add to dashboard Cite

Abstract-This work introduces the one-class slab SVM (OC-SSVM), a one-class classifier that aims at improving the performance of the one-class SVM. The proposed strategy reduces the false positive rate and increases the accuracy of detecting instances from novel classes. To this end, it uses two parallel hyperplanes to learn the normal region of the decision scores of the target class. OCSSVM extends one-class SVM since it can scale and learn non-linear decision functions via kernel methods. The experiments on two publicly available datasets show that OCSSVM can consistently outperform the one-class SVM and perform comparable to or better than other state-of-the-art oneclass classifiers.

show abstract

Section: Introductionmentioning

confidence: 99%

One-class slab support vector machine

Fragoso

Scheirer

Hespanha

et al. 2016

2016 23rd International Conference on Pattern Recognition (ICPR)

View full text Add to dashboard Cite

show abstract

“…There are many approaches proposed in the literature for the detection of exudates [2,3,4,5,6,7,8,9,10,11]. Some of them are discussed below.…”

Section: Literature Surveymentioning

confidence: 99%

“…T.Yamuna, S.Maheswari presents a new approach to detect abnormalities in the retinal images in this paper [2]. To detect the abnormality, two preprocessing and one candidate extraction method are proposed and various stages of abnormalities are classified based on the features like area, mean standard deviation, entropy etc.…”

Section: Literature Surveymentioning

confidence: 99%

“…Nowadays, diabetic retinopathy, glaucoma, and macular degeneration are the most common disease which causes visual impairment and blindness [2], [3].Early diagnosis and analysis of these diseases can prevent visual loss. Through regular ophthalmologic examination all of these diseases can be detected but due to increase number of patients, the number of ophthalmologists needed for evaluation by direct examination is a limiting factor.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of Diabetic Retinopathy by Detecting Exudates in the Retinal image

Kashyap¹

2018

IJCA

View full text Add to dashboard Cite

Retinal image investigation and processing has great significance in clinical study. Digital retinal photograph is widely used for screening of the patients suffering from diseases such as Diabetic Retinopathy and Glaucoma. A common issue of diabetes is diabetic eye disease. Diabetes is the most common disease in India. Timely diagnosis and management of these diseases can prevent severe visual loss. The proposed work will mainly deal with the detection of clinical components exudates from the retinal images, which are of prime importance in the clinical examination of diabetic patients for automated diagnosis of retinal diseases. The proposed method has been chosen in order to reduce the time consumption, cost for detection of such diseases and to provide an easy, simple and efficient way. The Sensitivity and Specificity of the proposed work for analysis of disease in the retinal images of the patients suffering from DR from local hospital (Sankaradeva Nethralaya) are 96.9% and 98.4% and for STARE database are 95% and 97.5% respectively.

show abstract

“…The exudates were determined using morphology techniques. T Yamuna et al [10] improved the quality of image using illumuination equalization and contrast limited adaptive equalization(CLAHE). Then candidate extraction is done using shade correction which uses pre processed image and green channel image.…”

Section: Literature Surveymentioning

confidence: 99%

Detection of Exudative Maculopathy from Retinal Fundus Images

Sreedevi¹,

Menon²

2014

IJCA

View full text Add to dashboard Cite

Diabetic retinopathy is a group of eye problems caused due to diabetes. Longer time a person has diabetes; the higher is his or her chances of developing diabetic retinopathy. One of the stages of diabetic retinopathy is Exudative Maculopathy. Spontaneous progression and regression of exudates causes Exudative Maculopathy.This work focuses on extraction of exudates from retinal fundus images using image processing techniques.

show abstract

Detection of abnormalities in retinal images

Cited by 12 publications

References 15 publications

One-class slab support vector machine

One-class slab support vector machine

Analysis of Diabetic Retinopathy by Detecting Exudates in the Retinal image

Detection of Exudative Maculopathy from Retinal Fundus Images

Contact Info

Product

Resources

About