Ashutosh Richhariya

Automated estimation of choroidal thickness distribution and volume based on OCT images of posterior visual section

A variety of vision ailments are indicated by anomalies in the choroid layer of the posterior visual section. Consequently, choroidal thickness and volume measurements, usually performed by experts based on optical coherence tomography (OCT) images, have assumed diagnostic significance. Now, to save precious expert time, it has become imperative to develop automated methods. To this end, one requires choroid outer boundary (COB) detection as a crucial step, where difficulty arises as the COB divides the choroidal granularity and the scleral uniformity only notionally, without marked brightness variation. In this backdrop, we measure the structural dissimilarity between choroid and sclera by structural similarity (SSIM) index, and hence estimate the COB by thresholding. Subsequently, smooth COB estimates, mimicking manual delineation, are obtained using tensor voting. On five datasets, each consisting of 97 adult OCT B-scans, automated and manual segmentation results agree visually. We also demonstrate close statistical match (greater than 99.6% correlation) between choroidal thickness distributions obtained algorithmically and manually. Further, quantitative superiority of our method is established over existing results by respective factors of 27.67% and 76.04% in two quotient measures defined relative to observer repeatability. Finally, automated choroidal volume estimation, being attempted for the first time, also yields results in close agreement with that of manual methods.

Fundus Photography in the 21st Century—A Review of Recent Technological Advances and Their Implications for Worldwide Healthcare

BACKGROUND The introduction of fundus photography has impacted retinal imaging and retinal screening programs significantly. LITERATURE REVIEW Fundus cameras play a vital role in addressing the cause of preventive blindness. More attention is being turned to developing countries, where infrastructure and access to healthcare are limited. One of the major limitations for tele-ophthalmology is restricted access to the office-based fundus camera. RESULTS Recent advances in access to telecommunications coupled with introduction of portable cameras and smartphone-based fundus imaging systems have resulted in an exponential surge in available technologies for portable fundus photography. Retinal cameras in the near future would have to cater to these needs by featuring a low-cost, portable design with automated controls and digitalized images with Web-based transfer. CONCLUSIONS In this review, we aim to highlight the advances of fundus photography for retinal screening as well as discuss the advantages, disadvantages, and implications of the various technologies that are currently available.

Investigation of alterations in multifractality in optical coherence tomographic images of in vivo human retina

Abstract. Optical coherence tomography (OCT) enables us to monitor alterations in the thickness of the retinal layer as disease progresses in the human retina. However, subtle morphological changes in the retinal layers due to early disease progression often may not lead to detectable alterations in the thickness. OCT images encode depth-dependent backscattered intensity distribution arising due to the depth distributions of the refractive index from tissue microstructures. Here, such depth-resolved refractive index variations of different retinal layers were analyzed using multifractal detrended fluctuation analysis, a special class of multiresolution analysis tools. The analysis extracted and quantified microstructural multifractal information encoded in normal as well as diseased human retinal OCT images acquired in vivo. Interestingly, different layers of the retina exhibited different degrees of multifractality in a particular retina, and the individual layers displayed consistent multifractal trends in healthy retinas of different human subjects. In the retinal layers of diabetic macular edema (DME) subjects, the change in multifractality manifested prominently near the boundary of the DME as compared to the normal retinal layers. The demonstrated ability to quantify depth-resolved information on multifractality encoded in OCT images appears promising for the early diagnosis of diseases of the human eye, which may also prove useful for detecting other types of tissue abnormalities from OCT images.

An automated algorithm for blood vessel count and area measurement in 2-D choroidal scan images

We present an automated algorithm for the detection of blood vessels in 2-D choroidal scan images followed by a measurement of the area of the vessels. The objective is to identify vessel parameters in the choroidal stroma that are affected by various abnormalities. The algorithm is divided into five stages. In the first stage, the image is denoised to remove sensor noise and facilitate further processing. In the second stage, the image is segmented in order to find the region of interest. In the third stage, three different contour detection methods are applied to address different challenges in vessel contour. In the fourth stage, the outputs of the three contour detection methods are combined to achieve refined vessel contour detection. In the fifth and final stage, the area of these contours are measured. The results have been evaluated by a practicing opthalmologist and performance of the algorithm relative to expert detection is reported.

Optical coherence tomography imaging: Automated binarization of choroid for stromal-luminal analysis

Structural changes in the choroid, interspersed between the retina and sclera, could indicate various vision impairments. So far, choroidal thickness and volume measured from optical coherence tomography (OCT) scans of the rear part of the eye have found clinical applications. However, such gross measurements do not provide vasculature-specific information crucial in managing various chorioretinal diseases. To fill this gap, we propose an automated method of ratiometric quantification of choroidal vascular (luminal) and interstitial (stromal) regions. Specifically, our method removes idiosyncratic artefacts of OCT imaging including speckle noise, exponential dynamic range compression, and depth-dependent attenuation in a targetted manner using median filtering and exponential enhancement. The proposed method assumed significance as manual estimation of the desired ratio is infeasible in view of the inherently fine structure of many choroidal vessels. Further, our technique demonstrated vast superiority over existing protocol based on the generic ImageJ software in terms of quality. Moreover, unlike the existing protocol which is interactive, our method could be applied to high-throuput and volumetric analysis.

Semi-automated quantification of retinal IS/OS damage in en-face OCT image

A variety of vision ailments are indicated by structural changes in the retinal substructures of the posterior segment of the eye. In particular, integrity of the inner-segment/outer-segment (IS/OS) junction directly relates to the visual acuity. In the en-face optical coherence tomography (OCT) image, IS/OS damage manifests as a dark spot in the foveal region, and its quantification, usually performed by experts, assumes diagnostic significance. In this context, in view of the general scarcity of experts, it becomes imperative to develop algorithmic methods to reduce expert time and effort. Accordingly, we propose a semi-automated method based on level sets. As the energy function, we adopt mutual information which exploits the difference in statistical properties of the lesion and its surroundings. On a dataset of 27 en-face OCT images, segmentation obtained by the proposed algorithm exhibits close visual agreement with that obtained manually. Importantly, our results also match manual results in various statistical criteria. In particular, we achieve a mean Dice coefficient of 85.69%, desirably close to the corresponding observer repeatability index of 89.45%. Finally, we quantify algorithmic accuracy in terms of two quotient measures, defined relative to observer repeatability, which could be used as bases for comparison with future algorithms, even if the latter are tested on disparate datasets.

Automated detection of choroid boundary and vessels in optical coherence tomography images

Structural changes in the choroid, a layer located between the retina and sclera, could indicate various vision impairments. Consequently, ophthalmologists inspect optical coherence tomography (OCT) scans of the posterior section of the eye towards making diagnosis. With a view to assist diagnosis, we propose an automated technique for segmentation of the choroid layer. Specifically, we detect the upper and lower boundaries of the choroid using structural similarity and adaptive Hessian analysis. Subsequently, we detect choroid vessels within those boundaries using a level set method. Experimental results are presented using spectral domain (SD) OCT images.

3D visualization and mapping of choroid thickness based on optical coherence tomography: A step-by-step geometric approach

Although bodily organs are inherently 3D, medical diagnosis often relies on their 2D representation. For instance, sectional images of the eye (especially, of its posterior part) based on optical coherence tomography (OCT) provide internal views, from which the ophthalmologist makes medical decisions about 3D eye structures. In the course, the physician is forced to mentally synthesize the underlying 3D context, which could be both time consuming and stressful. In this backdrop, can such 2D sections be arranged and presented in the natural 3D form for faster and stress-free diagnosis? In this paper, we consider ailments affecting choroid thickness, and address the aforementioned question at two levels-in terms of 3D visualization and 3D mapping. In particular, we exploit the spherical geometry of the eye, align OCT sections on a nominal sphere, and extract the choroid by peeling off inner and outer layers. At each step, we render our intermediate results on a 3D lightfield display, which provides a natural visual representation. Finally, the thickness variation of the extracted choroid is spatially mapped, and observed on a lightfield display as well as using 3D visualization softwares on a regular 2D terminal. Consequently, we identified choroid depletion around optic disc based on the test OCT images. We believe that the proposed technique would provide ophthalmologists with a tool for making faster diagnostic decisions with less stress.

Segmenting and Labeling blood vessels in choroidal Haller's layer: A multiple target tracking approach

In ophthalmology, monitoring of choroid health assumes significance as various diseases, including age-related macular degeneration, tend to affect choroidal vasculature early. However, associated changes are often minute, and it remains a challenge to locate those. The traditional method, where clinicians glance through multiple 2D OCT images to make a diagnosis, is often imprecise and unreliable. Hence, it is imperative to develop technology-assisted reliable methods to detect and precisely locate minute structural changes in 3D. The present paper takes an initial step towards meeting such imperative. Specifically, we adopt a multiple target tracking approach to trace blood vessel systems of relatively large diameters belonging to Hallers layer. We obtained high accuracy in terms of Dice coefficient for synthetic images, and subsequently presented our results for clinical OCT images. Our method facilitates localization of anomalies at the scale of blood vessels, potentially revolutionizing future clinical practice.

Oculofacial surgical planning: True-to-scale 3D feature quantification using multicamera network

3D surface imaging can potentially play a crucial role in oculofacial surgeries. Associated 3D measurements can facilitate surgical planning and postoperative assessment. Further, lifelike 3D visualization of human face is helpful as a communication/training tool for medical professionals/trainees. In this backdrop, we present a 3D surface imaging and measurement platform that is both flexible and accurate. Specifically, our systems consists of a stereo camera and two monocular cameras, which can be individually positioned and focused to obtain crisp images. From those images, true-to-scale reconstruction was achieved with accuracy levels between 97.46% and 99.83% in various oculofacial measurements. Significantly, such levels of accuracy are comparable to those achieved by inflexible legacy systems. Additionally, our system, consisting of discrete cameras, requires minimal training to operate, and hence could find use in telemedicine.