Fundus Images Of Preterm Infants Research Articles

AFENet: Attention Fusion Enhancement Network for Optic Disc Segmentation of Premature Infants.

Retinopathy of prematurity and ischemic brain injury resulting in periventricular white matter damage are the main causes of visual impairment in premature infants. Accurate optic disc (OD) segmentation has important prognostic significance for the auxiliary diagnosis of the above two diseases of premature infants. Because of the complexity and non-uniform illumination and low contrast between background and the target area of the fundus images, the segmentation of OD for infants is challenging and rarely reported in the literature. In this article, to tackle these problems, we propose a novel attention fusion enhancement network (AFENet) for the accurate segmentation of OD in the fundus images of premature infants by fusing adjacent high-level semantic information and multiscale low-level detailed information from different levels based on encoder–decoder network. Specifically, we first design a dual-scale semantic enhancement (DsSE) module between the encoder and the decoder inspired by self-attention mechanism, which can enhance the semantic contextual information for the decoder by reconstructing skip connection. Then, to reduce the semantic gaps between the high-level and low-level features, a multiscale feature fusion (MsFF) module is developed to fuse multiple features of different levels at the top of encoder by using attention mechanism. Finally, the proposed AFENet was evaluated on the fundus images of preterm infants for OD segmentation, which shows that the proposed two modules are both promising. Based on the baseline (Res34UNet), using DsSE or MsFF module alone can increase Dice similarity coefficients by 1.51 and 1.70%, respectively, whereas the integration of the two modules together can increase 2.11%. Compared with other state-of-the-art segmentation methods, the proposed AFENet achieves a high segmentation performance.

A deep learning framework for the detection of Plus disease in retinal fundus images of preterm infants

Retinopathy of prematurity (ROP) is an eye disorder that mainly affects fundus vasculature of immature infants. The effect of this disease can be mild with no observable impairments or may become severe with neovascularization, leading to retinal detachment and possibly childhood blindness. A vital sign for initiating treatment for ROP is the detection of Plus disease, which is clinically diagnosed by identifying certain morphological changes to the blood vessels present in the retina of preterm infants. The main goal of this study is to develop a diagnostic method that can distinguish between Plus-diseased and healthy infant retinal images. This work utilizes a fully convolutional deep learning architecture for achieving the desired objective. We use a semi-supervised learning technique for training the network. The proposed technique accurately predicts bounding boxes over the tortuous vessel segments present in an infant retinal image. The count of bounding boxes serve as a measure to quantify tortuosity. We also compare the proposed technique with a recently introduced ROP diagnostic method employing U-COSFIRE filters. We show the efficacy of the proposed methodology on a proprietary data set of 289 infant retinal images (89 with ROP, and 200 healthy), obtained from KIDROP Bangalore, India. We obtain sensitivity (true positive rate) and specificity (true negative rate) equal to 0.99 and 0.98, respectively in the experimented data set. The results obtained in this study show the robustness of the proposed pipeline, as a computer aided diagnostic tool, that can augment medical experts in the early diagnosis of ROP.

U-COSFIRE filters for vessel tortuosity quantification with application to automated diagnosis of retinopathy of prematurity

Retinopathy of prematurity (ROP) is a sight threatening disorder that primarily affects preterm infants. It is the major reason for lifelong vision impairment and childhood blindness. Digital fundus images of preterm infants obtained from a Retcam Ophthalmic Imaging Device are typically used for ROP screening. ROP is often accompanied by Plus disease that is characterized by high levels of arteriolar tortuosity and venous dilation. The recent diagnostic procedures view the prevalence of Plus disease as a factor of prognostic significance in determining its stage, progress and severity. Our aim is to develop a diagnostic method, which can distinguish images of retinas with ROP from healthy ones and that can be interpreted by medical experts. We investigate the quantification of retinal blood vessel tortuosity via a novel U-COSFIRE (Combination Of Shifted Filter Responses) filter and propose a computer-aided diagnosis tool for automated ROP detection. The proposed methodology involves segmentation of retinal blood vessels using a set of B-COSFIRE filters with different scales followed by the detection of tortuous vessels in the obtained vessel map by means of U-COSFIRE filters. We also compare our proposed technique with an angle-based diagnostic method that utilizes the magnitude and orientation responses of the multi-scale B-COSFIRE filters. We carried out experiments on a new data set of 289 infant retinal images (89 with ROP and 200 healthy) that we collected from the programme in India called KIDROP (Karnataka Internet Assisted Diagnosis of Retinopathy of Prematurity). We used 10 images (5 with ROP and 5 healthy) for learning the parameters of our methodology and the remaining 279 images (84 with ROP and 195 healthy) for performance evaluation. We achieved sensitivity and specificity equal to 0.98 and 0.97, respectively, computed on the 279 test images. The obtained results and its explainable character demonstrate the effectiveness of the proposed approach to assist medical experts.

Comparison of optic disk features in preterm and term infants

To compare the optic disk features of preterm and term infants. Digital fundus images of preterm infants were compared with those of infants born at term, imaged within 1week of birth. The optic disk horizontal diameter to vertical diameter ratio, the disk-macula to disk-diameter ratio, and the presence or absence of double ring sign was noted. Images of 649 infants (324 preterm and 325 term) were analyzed. Of the preterm infants, 129 (40%) had a double ring sign, compared to 4% in term infants. The double ring was seen more frequently in infants of European descent and was more common with younger gestational age. The mean horizontal to vertical disk diameter in preterm infants on first examination was 0.75±0.063, increasing to 0.80±0.069 at final examination. Term infants had a horizontal to vertical disk diameter ratio of 0.79±0.064. At final examination, the ratio of disk-to-macula distance to the horizontal disk diameter was 3.9 in preterm infants and 3.7 for term infants. In our study population preterm infants often had a double ring sign around the optic disk in the absence of optic nerve hypoplasia. Preterm disks tend to be more vertically oval, which becomes less oval closer to term. The mean disk-to-macula to disk-diameter ratio among normal preterm infants was higher than previously reported.

Computer-aided diagnosis of retinopathy in retinal fundus images of preterm infants via quantification of vascular tortuosity.

Retinopathy of prematurity (ROP), a disorder of the retina occurring in preterm infants, is the leading cause of preventable childhood blindness. An active phase of ROP that requires treatment is associated with the presence of plus disease, which is diagnosed clinically in a qualitative manner by visual assessment of the existence of a certain level of increase in the thickness and tortuosity of retinal vessels. The present study performs computer-aided diagnosis (CAD) of plus disease via quantitative measurement of tortuosity in retinal fundus images of preterm infants. Digital image processing techniques were developed for the detection of retinal vessels and measurement of their tortuosity. The total lengths of abnormally tortuous vessels in each quadrant and the entire image were then computed. A minimum-length diagnostic-decision-making criterion was developed to assess the diagnostic sensitivity and specificity of the values obtained. The area ([Formula: see text]) under the receiver operating characteristic curve was used to assess the overall diagnostic accuracy of the methods. Using a set of 19 retinal fundus images of preterm infants with plus disease and 91 without plus disease, the proposed methods provided an overall diagnostic accuracy of [Formula: see text]. Using the total length of all abnormally tortuous vessel segments in an image, our techniques are capable of CAD of plus disease with high accuracy without the need for manual selection of vessels to analyze. The proposed methods may be used in a clinical or teleophthalmological setting.

Computer-aided diagnosis of plus disease via measurement of vessel thickness in retinal fundus images of preterm infants

Changes in the characteristics of retinal vessels such as width and tortuosity can be signs of the presence of several diseases such retinopathy of prematurity (ROP) and diabetic retinopathy. Plus disease is an indicator of ROP which requires treatment and is signified by an increase in posterior venular width. In this work, we present image processing techniques for the detection, segmentation, tracking, and measurement of the width of the major temporal arcade (MTA), which is the thickest venular branch in the retina. Several image processing techniques have been employed, including the use of Gabor filters to detect the MTA, morphological image processing to obtain its skeleton, Canny׳s method to detect and select MTA vessel-edge candidates, least-squares fitting to interpolate the MTA edges, and geometrical procedures to measure the width of the MTA. The results, obtained using 110 retinal fundus images of preterm infants, indicate a statistically highly significant difference in MTA width of normal cases as compared to cases with plus disease (p<0.01). The results provide good accuracy in computer-aided diagnosis (CAD) of plus disease with an area under the receiver operating characteristic curve of 0.76. The proposed methods may be used in CAD of plus disease and timely treatment of ROP in a clinical or teleophthalmological setting.

Computer-aided diagnosis of plus disease in retinal fundus images of preterm infants via measurement of vessel tortuosity.

An increase in retinal vessel tortuosity can be indicative of the presence of various diseases including retinopathy of prematurity (ROP). Accurate detection and measurement of such changes could help in computer-aided diagnosis of plus disease, which warrants treatment of ROP. We present image processing methods for detection and segmentation of retinal vessels, quantification of vessel tortuosity, and diagnostic-decision-making criteria that incorporate the clinical definition of plus-diagnosis. The obtained results using 110 retinal fundus images of preterm infants (91 without plus and 19 with plus) provide high sensitivity = 0.89 (17/19) and excellent specificity = 0.95 (86/91) in the diagnosis of plus disease.

Quantification of the changes in the openness of the major temporal arcade in retinal fundus images of preterm infants with plus disease.

We tested the hypothesis that the openness of the major temporal arcade (MTA) changes in the presence of plus disease, by quantification via parabolic modeling of the MTA, as well as measurement of an arcade angle for comparative analysis. Such analysis could assist in the detection and treatment of progressive retinopathy of prematurity. Digital image processing techniques were applied for the detection and modeling of the MTA via a graphical user interface (GUI) to quantify the openness of the MTA. An arcade angle measure, based on a previously proposed method, also was obtained via the GUI for comparative analysis. The statistical significance of the differences between the plus and no-plus cases for each parameter was analyzed using the P value. The area (Az) under the receiver operating characteristic curve was used to assess the diagnostic performance of each feature. The temporal arcade angle measure and the openness parameter of the parabolic model were used to perform discrimination of plus versus no-plus cases. Using a set of 19 cases with plus and 91 with no plus disease, Az=0.70 was obtained using the results of dual-parabolic modeling in screening for plus disease. The arcade angle measure provided comparable results with Az=0.73. Using our proposed image analysis techniques and software, this study demonstrates, for the first time to our knowledge, that the openness of the MTA decreases in the presence of plus disease.

Assessment of vessel tortuosity in retinal images of preterm infants.

Diagnosis of plus disease is crucial for timely treatment and management of retinopathy of prematurity. An indicator of the presence of plus disease is an increase in the tortuosity of blood vessels in the retina. In this work, we propose a new angle-variation-based measure for quantification of tortuosity in retinal fundus images of preterm infants. The methods include the use of Gabor filters to detect vessels as well as to obtain their orientation at each pixel. Morphological image processing methods are used to obtain a skeleton image of the vessels for measurement of tortuosity. Out of 11 vessel segments, marked by an expert ophthalmologist as showing high levels of tortuosity due to plus disease, all were correctly identified using the proposed methods.