Search results for: fundus

Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: Diabetic retinopathy, fundus, CHT, exudates, hemorrhages.

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Authors: Pil Un Kim, Yunjung Lee, Gihyoun Lee, Jin Ho Cho, Myoung Nam Kim

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In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.

Keywords: Angle measurement, Optic disc, Retina vessel, Vessel progression orientation.

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Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: Ocular diseases, retinal fundus image, optic disc detection and segmentation, fully convolutional network, overlap measure.

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Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong

Abstract:

Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

Keywords: Glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection.

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Authors: Naoto Suzuki

Abstract:

Japanese are affected by the most common causes of eyesight loss such as glaucoma, diabetic retinopathy, pigmentary retinal degeneration, and age-related macular degeneration. We developed an ophthalmological examination apparatus with a fundus camera, precisely fundus-related perimetry (microperimetry), and electroretinogram (ERG) functions to diagnose a variety of diseases that cause eyesight loss. The experimental apparatus was constructed with the same optical system as a fundus camera. The microperimetry optical system was calculated and added to the experimental apparatus using the German company Optenso's optical engineering software (OpTaliX-LT 10.8). We also added an Edmund infrared camera (EO-0413), a lens with a 25 mm focal length, a 45° cold mirror, a 12 V/50 W halogen lamp, and an 8-inch monitor. We made the artificial eye of a plane-convex lens, a black spacer, and a hemispherical cup. The hemispherical cup had a small section of the paper at the bottom. The artificial eye was photographed five times using the experimental apparatus. The software was created to display the examination target on the monitor and save examination data using C++Builder 10.2. The retinal fundus was displayed on the monitor at a length and width of 1 mm and a resolution of 70.4 ± 4.1 and 74.7 ± 6.8 pixels, respectively. The microperimetry and ERG functions were successfully added to the experimental ophthalmological apparatus. A moving machine was developed to measure the artificial eye's movement. The artificial eye's rear part was painted black and white in the central area. It was rotated 10 degrees from one side to the other. The movement was captured five times as motion videos. Three static images were extracted from one of the motion videos captured. The images display the artificial eye facing the center, right, and left directions. The three images were processed using Scilab 6.1.0 and Image Processing and Computer Vision Toolbox 4.1.2, including trimming, binarization, making a window, deleting peripheral area, and morphological operations. To calculate the artificial eye's fundus center, we added a gravity method to the program to calculate the gravity position of connected components. From the three images, the image processing could calculate the center position.

Keywords: Ophthalmological examination apparatus, microperimetry, electroretinogram, eye movement.

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Authors: Srinivasan Aruchamy, Partha Bhattacharjee, Goutam Sanyal

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Optic disk segmentation plays a key role in the mass screening of individuals with diabetic retinopathy and glaucoma ailments. An efficient hardware-based algorithm for optic disk localization and segmentation would aid for developing an automated retinal image analysis system for real time applications. Herein, TMS320C6416DSK DSP board pixel intensity based fractal analysis algorithm for an automatic localization and segmentation of the optic disk is reported. The experiment has been performed on color and fluorescent angiography retinal fundus images. Initially, the images were pre-processed to reduce the noise and enhance the quality. The retinal vascular tree of the image was then extracted using canny edge detection technique. Finally, a pixel intensity based fractal analysis is performed to segment the optic disk by tracing the origin of the vascular tree. The proposed method is examined on three publicly available data sets of the retinal image and also with the data set obtained from an eye clinic. The average accuracy achieved is 96.2%. To the best of the knowledge, this is the first work reporting the use of TMS320C6416DSK DSP board and pixel intensity based fractal analysis algorithm for an automatic localization and segmentation of the optic disk. This will pave the way for developing devices for detection of retinal diseases in the future.

Keywords: Color retinal fundus images, Diabetic retinopathy, Fluorescein angiography retinal fundus images, Fractal analysis.

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Authors: Naoto Suzuki

Abstract:

Many ophthalmologists find it difficult to distinguish between small retinal hemorrhages and dust artifacts when using fundus photography for the diagnosis of diabetic retinopathy. Six patients with diabetic retinopathy underwent fundus photography, which revealed dust artifacts in the photographs of some patients. We constructed an experimental device similar to the optical system of the fundus camera and colored the fundi of the artificial eyes with khaki, sunset, rose and sunflower colors. Using the experimental device, we photographed dust artifacts using each artificial eyes. We used Scilab 5.4.0 and SIVP 0.5.3 softwares to convert the red, green, and blue (RGB) color space to the hue, saturation, and value (HSV) color space. We calculated the differences between the areas of manifestations and perimanifestations and the areas of dust artifacts and periartifacts using average HSVs. The V values in HSV for the manifestations were as follows: hemorrhages, 0.06 ± 0.03; hard exudates, −0.12 ± 0.06; and photocoagulation marks, 0.07 ± 0.02. For dust artifacts, visualized in the human and artificial eyes, the V values were as follows: human eye, 0.19 ± 0.03; khaki, 0.41 ± 0.02; sunset, 0.43 ± 0.04; rose, 0.47 ± 0.11; and sunflower, 0.59 ± 0.07. For the human and artificial eyes, we calculated two sensitivity values of dust artifacts compared to manifestation areas. V values of the HSV color space enabled the differentiation of small hemorrhages, hard exudates, and photocoagulation marks from dust artifacts.

Keywords: Diabetic retinopathy, HSV color space, small hemorrhages, hard exudates, photocoagulation marks.

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe V. Lakshminarayanan, K. Raahemifar

Abstract:

Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: Diabetic retinopathy, fundus images, STARE, Gabor filter, SVM.

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Authors: Naoto Suzuki

Abstract:

To distinguish small retinal hemorrhages in early diabetic retinopathy from dust artifacts, we analyzed hue, lightness, and saturation (HLS) color spaces. The fundus of 5 patients with diabetic retinopathy was photographed. For the initial experiment, we placed 4 different colored papers on the ceiling of a darkroom. Using each color, 10 fragments of house dust particles on a magnifier were photographed. The colored papers were removed, and 3 different colored light bulbs were suspended from the ceiling. Ten fragments of house dust particles on the camera-s object lens were photographed. We then constructed an experimental device that can photograph artificial eyes. Five fragments of house dust particles under the ocher fundus of the artificial eye were photographed. On analyzing HLS color space of the dust artifact, lightness and saturation were found to be highly sensitive. However, hue was not highly sensitive.

Keywords: Dust artifact, HLS color space, Retinal hemorrhage, and Diabetic retinopathy

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Authors: Noor Elaiza Abdul Khalid, Noorhayati Mohamed Noor, Zamalia Mahmud, Saadiah Yahya, and Norharyati Md Ariff

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Glaucoma diagnosis involves extracting three features of the fundus image; optic cup, optic disc and vernacular. Present manual diagnosis is expensive, tedious and time consuming. A number of researches have been conducted to automate this process. However, the variability between the diagnostic capability of an automated system and ophthalmologist has yet to be established. This paper discusses the efficiency and variability between ophthalmologist opinion and digital technique; threshold. The efficiency and variability measures are based on image quality grading; poor, satisfactory or good. The images are separated into four channels; gray, red, green and blue. A scientific investigation was conducted on three ophthalmologists who graded the images based on the image quality. The images are threshold using multithresholding and graded as done by the ophthalmologist. A comparison of grade from the ophthalmologist and threshold is made. The results show there is a small variability between result of ophthalmologists and digital threshold.

Keywords: Digital Fundus Image, Glaucoma Detection, Multithresholding, Segmentation.

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Authors: Naoto Suzuki

Abstract:

Many ophthalmologists can examine declines in visual sensitivity at arbitrary points on the retina using a precise perimetry device with a fundus camera function. However, the retinal layer causing the decline in visual sensitivity cannot be identified by this method. We studied an electroretinogram (ERG) function that can move the center of the multifocal hexagonal stimulus array in order to investigate cryptogenic diseases, such as macular dystrophy, acute zonal occult outer retinopathy, and multiple evanescent white dot syndrome. An electroretinographic optical system, specifically a perimetric optical system, was added to an experimental device carrying the same optical system as a fundus camera. We also added an infrared camera, a cold mirror, a halogen lamp, and a monitor. The software was generated to show the multifocal hexagonal stimulus array on the monitor using C++Builder XE8 and to move the center of the array up and down as well as back and forth. We used a multifunction I/O device and its design platform LabVIEW for data retrieval. The plate electrodes were used to measure electrodermal activities around the eyes. We used a multifocal hexagonal stimulus array with 37 elements in the software. The center of the multifocal hexagonal stimulus array could be adjusted to the same position as the examination target of the precise perimetry. We successfully added the moving ERG function to the experimental ophthalmologic device.

Keywords: Moving ERG, precise perimetry, retinal layers, visual sensitivity.

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Authors: Khaled M. Ali, M. A. Abdel-Hamid, Ayman A. Mostafa

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Objective: Safety and efficacy of Ahmed glaucoma valve implantation for the management of uveitis induced glaucoma evaluated on the five dogs with uncontrollable glaucoma. Materials and Methods: Ahmed Glaucoma Valve (AGV®; New World Medical, Rancho Cucamonga, CA, USA) is a flow restrictive, nonobstructive self-regulating valve system. Preoperative ocular evaluation included direct ophthalmoscopy and measurement of the intraocular pressure (IOP). The implant was examined and primed prior to implantation. The selected site of the valve implantation was the superior quadrant between the superior and lateral rectus muscles. A fornix-based incision was made through the conjunectiva and Tenon’s capsule. A pocket is formed by blunt dissection of Tenon’s capsule from the episclera. The body of the implant was inserted into the pocket with the leading edge of the device around 8-10 mm from the limbus. Results: No post-operative complications were detected in the operated eyes except a persistent corneal edema occupied the upper half of the cornea in one case. Hyphaema was very mild and seen only in two cases which resolved quickly two days after surgery. Endoscopical evaluation for the operated eyes revealed a normal ocular fundus with clearly visible optic papilla, tapetum and retinal blood vessels. No evidence of hemorrhage, infection, adhesions or retinal abnormalities was detected. Conclusion: Ahmed glaucoma valve is safe and effective implant for treatment of uveitic glaucoma in dogs.

Keywords: Ahmed valve, endoscopy, glaucoma, ocular fundus.

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Authors: Naoto Suzuki

Abstract:

A decline in visual sensitivity at arbitrary points on the retina can be measured using a precise perimetry apparatus along with a fundus camera. However, the retinal layer associated with this decline cannot be identified accurately with current medical technology. To investigate cryptogenic diseases, such as macular dystrophy, acute zonal occult outer retinopathy (AZOOR), and multiple evanescent white dot syndrome (MEWDS), we evaluated an electroretinogram (ERG) function that allows moving the center of the multifocal hexagonal stimulus array to a chosen position. Macular dystrophy is a generalized term used for a variety of functional disorders of the macula lutea, and the ERG shows a diminution of the b-wave in these disorders. AZOOR causes an acute functional disorder to an outer layer of the retina, and the ERG shows a-wave and b-wave amplitude reduction as well as delayed 30 Hz flicker responses. MEWDS causes acute visual loss and the ERG shows a decrease in a-wave amplitude. We combined an electroretinographic optical system and a perimetric optical system into an experimental apparatus that has the same optical system as that of a fundus camera. We also deployed an EO-50231 Edmund infrared camera, a 45-degree cold mirror, a lens with a 25-mm focal length, a halogen lamp, and an 8-inch monitor. Then, we also employed a differential amplifier with gain 10, a 50 Hz notch filter, a high-pass filter with a 21.2 Hz cut-off frequency, and two non-inverting amplifiers with gains 1001 and 11. In addition, we used a USB-6216 National Instruments I/O device, a NE-113A Nihon Kohden plate electrode, a SCB-68A shielded connector block, and LabVIEW 2017 software for data retrieval. The software was used to generate the multifocal hexagonal stimulus array on the computer monitor with C++Builder 10.2 and to move the center of the array toward the left and right and up and down. Cone and bright flash ERG results were observed using the moving ERG function. The a-wave, b-wave, c-wave, and the photopic negative response were identified with cone ERG. The moving ERG function allowed the identification of the retinal layer causing visual alterations.

Keywords: Moving ERG, multifocal ERG, precise perimetry, retinal layers, visual sensitivity

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Authors: M. Das Gupta, S. Banerjee

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Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.

Keywords: Case based reasoning, Exudates, Retina image, Similarity based retrieval.

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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