Arun Brahma

Objective morphological assessment of macular hole surgery by scanning laser tomography

AIM To assess the morphological change in retinal topography using a scanning laser tomographer following macular hole surgery. To compare the results of scanning laser tomography with clinical evaluation and visual function assessment. METHODS The sample for this pilot study comprised four eyes exhibiting different stages of macular hole formation preoperatively. Subjects were assessed preoperatively and at 1 and 3 months postoperatively. Each assessment included visual acuity, letter contrast sensitivity, clinical examination (including automated static perimetry), and scanning laser tomography. The Heidelberg retina tomograph (HRT) was used to acquire digitised scanning laser tomography images of the macula (10° and 20° fields). Surgery essentially comprised vitrectomy, peeling of the posterior hyaloid face, if still attached, and intraocular gas tamponade. The magnitude and significance of topographic change were determined postoperatively using the HRT topographic difference facility. RESULTS Topographic difference analysis of the right and left eyes of case 1 showed a significant reduction in the height of the retina postoperatively. Topographic difference analysis of case 2 showed no significant change in topography. Topographic difference analysis of case 3 showed a significant increase in the height of the retina postoperatively. Scanning laser tomography agreed with clinical assessment based upon fundus biomicroscopy in three of the four eyes studied; the postoperative closure of the stage 2 macular hole (as noted by clinical assessment) proved to be too small to reach statistical significance. Scanning laser tomography agreed with the assessment of visual function in two eyes; the agreement between scanning laser tomography and visual function depends, in part, on the stage of development of the macular hole. CONCLUSION Scanning laser tomography provides an objective evaluation of the outcome of macular hole surgery. Studies employing larger sample sizes are required to fully determine the clinical worth of the technique.

An efficient intelligent analysis system for confocal corneal endothelium images

A confocal microscope provides a sequence of images of the corneal layers and structures at different depths from which medical clinicians can extract clinical information on the state of health of the patients cornea. A hybrid model based on snake and particle swarm optimisation (S-PSO) is proposed in this paper to analyse the confocal endothelium images. The proposed system is able to pre-process images (including quality enhancement and noise reduction), detect cells, measure cell densities and identify abnormalities in the analysed data sets. Three normal corneal data sets acquired using a confocal microscope, and three abnormal confocal endothelium images associated with diseases have been investigated in the proposed system. Promising results are presented and the performance of this system is compared with manual and two morphological based approaches. The average differences between the manual and the automatic cell densities calculated using S-PSO and two other morphological based approaches is 5%, 7% and 13% respectively. The developed system will be deployable as a clinical tool to underpin the expertise of ophthalmologists in analysing confocal corneal images.

Biomechanical changes after repeated collagen cross-linking on human corneas assessed in vitro using scanning acoustic microscopy

PURPOSEnTo explore the biomechanical changes induced by repeated cross-linking using scanning acoustic microscopy (SAM).nnnMETHODSnThirty human corneas were divided into three groups. In group A, five corneas were cross-linked once. In group B, five corneas were cross-linked twice, 24 hours apart. In group C, five corneas were cross-linked three times, 24 hours apart. The contralateral controls in all groups had similar treatment but without UV-A. The speed of sound, which is directly proportional to the square root of the tissues elastic modulus, was assessed using SAM.nnnRESULTSnIn group A, the speed of sound of the treated corneas was 1677.38 ± 10.70 ms(-1) anteriorly and 1603.90 ± 9.82 ms(-1) posteriorly, while it was 1595.23 ± 9.66 ms(-1) anteriorly and 1577.13 ± 8.16 ms(-1) posteriorly in the controls. In group B, the speed of sound of the treated corneas was 1746.33 ± 23.37 ms(-1) anteriorly and 1631.60 ± 18.92 ms(-1) posteriorly, while it was 1637.57 ± 22.15 ms(-1) anteriorly and 1612.30 ± 22.23 ms(-1) posteriorly in the controls. In group C, the speed of sound of the treated corneas was 1717.97 ± 18.92 ms(-1) anteriorly and 1616.62 ± 17.58 ms(-1) posteriorly, while it was 1628.69 ± 9.37 ms(-1) anteriorly and 1597.68 ± 11.97 ms(-1) posteriorly in the controls. The speed of sound in the anterior (200 × 200 μm) region between the cross-linked and control corneas in groups A, B, and C was increased by a factor of 1.051 (P = 0.005), 1.066 (P = 0.010), and 1.055 (P = 0.005) respectively. However, there was no significant difference among the cross-linked corneas in all groups (P = 0.067).nnnCONCLUSIONSnA significant increase in speed of sound was found in all treated groups compared with the control group; however, the difference among the treated groups is not significant, suggesting no further cross-links are induced when collagen cross-linking treatment is repeated.

Medical image classification based on artificial intelligence approaches

A new intelligent system to tackle the main challenges of confocal corneal imaging is developed.This system underpins the expertise of ophthalmologists.It provides clinically useful factors, saves a useful amount of clinician time in the process.It is able to model the stromal keratocyte cells for better evaluation and fast analysis.Early approval by corneal clinicians. Corneal images can be acquired using confocal microscopes which provide detailed views of the different layers inside a human cornea. Some corneal problems and diseases can occur in one or more of the main corneal layers: the epithelium, stroma and endothelium. Consequently, for automatically extracting clinical information associated with corneal diseases, identifying abnormality or evaluating the normal cornea, it is important to be able to automatically recognise these layers reliably. Artificial intelligence (AI) approaches can provide improved accuracy over the conventional processing techniques and save a useful amount of time over the manual analysis time required by clinical experts. Artificial neural networks (ANNs), adaptive neuro fuzzy inference systems (ANFIS) and a committee machine (CM) have been investigated and tested to improve the recognition accuracy of the main corneal layers and identify abnormality in these layers. The performance of the CM, formed from ANN and ANFIS, achieves an accuracy of 100% for some classes in the processed data sets. Three normal corneal data sets and seven abnormal corneal images associated with diseases in the main corneal layers have been investigated with the proposed system. Statistical analysis for these data sets is performed to track any change in the processed images. This system is able to pre-process (quality enhancement, noise removal), classify corneal images, identify abnormalities in the analysed data sets and visualise corneal stroma images as well as each individual keratocyte cell in a 3D volume for further clinical analysis.

A fully automatic nerve segmentation and morphometric parameter quantification system for early diagnosis of diabetic neuropathy in corneal images

Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the nerve structures can assist the early diagnosis of this disease. This paper proposes a robust, fast and fully automatic nerve segmentation and morphometric parameter quantification system for corneal confocal microscope images. The segmentation part consists of three main steps. First, a preprocessing step is applied to enhance the visibility of the nerves and remove noise using anisotropic diffusion filtering, specifically a Coherence filter followed by Gaussian filtering. Second, morphological operations are applied to remove unwanted objects in the input image such as epithelial cells and small nerve segments. Finally, an edge detection step is applied to detect all the nerves in the input image. In this step, an efficient algorithm for connecting discontinuous nerves is proposed. In the morphometric parameters quantification part, a number of features are extracted, including thickness, tortuosity and length of nerve, which may be used for the early diagnosis of diabetic polyneuropathy and when planning Laser-Assisted in situ Keratomileusis (LASIK) or Photorefractive keratectomy (PRK). The performance of the proposed segmentation system is evaluated against manually traced ground-truth images based on a database consisting of 498 corneal sub-basal nerve images (238 are normal and 260 are abnormal). In addition, the robustness and efficiency of the proposed system in extracting morphometric features with clinical utility was evaluated in 919 images taken from healthy subjects and diabetic patients with and without neuropathy. We demonstrate rapid (13 seconds/image), robust and effective automated corneal nerve quantification. The proposed system will be deployed as a useful clinical tool to support the expertise of ophthalmologists and save the clinician time in a busy clinical setting.

Biomechanical Changes of Collagen Cross-Linking on Human Keratoconic Corneas Using Scanning Acoustic Microscopy.

ABSTRACT Purpose: To assess the biomechanical changes of collagen cross-linking on keratoconic corneas in vitro. Methods: Six keratoconic corneal buttons were included in this study. Each cornea was divided into two halves, where one half was cross-linked and the other half was treated with riboflavin only and served as control. The biomechanical changes of the corneal tissue were measured across the stroma using scanning acoustic microscopy (SAM). Results: In the cross-linked corneas, there was a steady decrease in the magnitude of speed of sound from the anterior region through to the posterior regions of the stroma. The speed of sound was found to decrease slightly across the corneal thickness in the control corneas. The increase in speed of sound between the cross-linked and control corneas in the anterior region was by a factor of 1.039×. Conclusion: A higher speed of sound was detected in cross-linked keratoconic corneal tissue when compared with their controls, using SAM. This in vitro model can be used to compare to the cross-linking results obtained in vivo, as well as comparing the results obtained with different protocols.

In vivo confocal microscopic corneal images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: a review study.

There is an evolution in the demands of modern ophthalmology from descriptive findings to assessment of cellular-level changes by using in vivo confocal microscopy. Confocal microscopy, by producing greyscale images, enables a microstructural insight into the in vivo cornea in both health and disease, including epithelial changes, stromal degenerative or dystrophic diseases, endothelial pathologies and corneal deposits and infections. Ophthalmologists use acquired confocal corneal images to identify health and disease states and then to diagnose which type of disease is affecting the cornea. This paper presents the main features of the healthy confocal corneal layers and reviews the most common corneal diseases. It identifies the visual signatures of each disease in the affected layer and extracts the main features of this disease in terms of intensity, certain regular shapes with both their size and diffusion, and some specific region of interest. These features will lead towards the development of a complete automatic corneal diagnostic system that predicts abnormalities in the confocal corneal data sets.

An efficient system for preprocessing confocal corneal images for subsequent analysis

A confocal microscope provides a sequence of images of the various corneal layers and structures at different depths from which medical clinicians can extract clinical information on the state of health of the patients cornea. Preprocessing the confocal corneal images to make them suitable for analysis is very challenging due the nature of these images and the amount of the noise present in them. This paper presents an efficient preprocessing approach for confocal corneal images consisting of three main steps including enhancement, binarisation and refinement. Improved visualisation, cell counts and measurements of cell properties have been achieved through this system and an interactive graphical user interface has been developed.

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology

BACKGROUND AND OBJECTIVEnCorneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy.nnnMETHODSnFirst, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (nu202f=u202f11), obese subjects (nu202f=u202f16) and patients with diabetes (nu202f=u202f13).nnnRESULTSnThe Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (pu202f<u202f0.0001) and a Bland-Altman plot shows that 95% of the data are between the 2SD agreement lines.nnnCONCLUSIONSnWe demonstrate the effectiveness and robustness of the CEAS system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image.

Biomechanical Changes After Repeated Collagen Cross-Linking on Human Corneas Assessed In Vitro Using Scanning Acoustic MicroscopyChanges After Repeated Collagen Cross-Linking

PURPOSEnTo explore the biomechanical changes induced by repeated cross-linking using scanning acoustic microscopy (SAM).nnnMETHODSnThirty human corneas were divided into three groups. In group A, five corneas were cross-linked once. In group B, five corneas were cross-linked twice, 24 hours apart. In group C, five corneas were cross-linked three times, 24 hours apart. The contralateral controls in all groups had similar treatment but without UV-A. The speed of sound, which is directly proportional to the square root of the tissues elastic modulus, was assessed using SAM.nnnRESULTSnIn group A, the speed of sound of the treated corneas was 1677.38 ± 10.70 ms(-1) anteriorly and 1603.90 ± 9.82 ms(-1) posteriorly, while it was 1595.23 ± 9.66 ms(-1) anteriorly and 1577.13 ± 8.16 ms(-1) posteriorly in the controls. In group B, the speed of sound of the treated corneas was 1746.33 ± 23.37 ms(-1) anteriorly and 1631.60 ± 18.92 ms(-1) posteriorly, while it was 1637.57 ± 22.15 ms(-1) anteriorly and 1612.30 ± 22.23 ms(-1) posteriorly in the controls. In group C, the speed of sound of the treated corneas was 1717.97 ± 18.92 ms(-1) anteriorly and 1616.62 ± 17.58 ms(-1) posteriorly, while it was 1628.69 ± 9.37 ms(-1) anteriorly and 1597.68 ± 11.97 ms(-1) posteriorly in the controls. The speed of sound in the anterior (200 × 200 μm) region between the cross-linked and control corneas in groups A, B, and C was increased by a factor of 1.051 (P = 0.005), 1.066 (P = 0.010), and 1.055 (P = 0.005) respectively. However, there was no significant difference among the cross-linked corneas in all groups (P = 0.067).nnnCONCLUSIONSnA significant increase in speed of sound was found in all treated groups compared with the control group; however, the difference among the treated groups is not significant, suggesting no further cross-links are induced when collagen cross-linking treatment is repeated.