Exploiting Reliability-Guided Aggregation for the Assessment of Curvilinear Structure Tortuosity

The study on tortuosity of curvilinear structures in medical images has been significant in support of the examination and diagnosis for a number of diseases. To avoid the bias that may arise from using one particular tortuosity measurement, the simultaneous use of multiple measurements may offer a promising approach to produce a more robust overall assessment. As such, this paper proposes a data-driven approach for the automated grading of curvilinear structures’ tortuosity, where multiple morphological measurements are aggregated on the basis of reliability to form a robust overall assessment. The proposed pipeline starts dealing with the imprecision and uncertainty inherently embedded in empirical tortuosity grades, whereby a fuzzy clustering method is applied on each available measurement. The reliability of each measurement is then assessed following a nearest neighbour guided approach before the final aggregation is made. Experimental results on two corneal nerve and one retinal vessel data sets demonstrate the superior performance of the proposed method over those where measurements are used independently or aggregated using conventional averaging operators

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

High-Resolution Optical Coherence Tomography Findings of Lisch Epithelial Corneal Dystrophy

PURPOSE: To describe a case of Lisch epithelial corneal dystrophy (LECD) and present its unique characteristics on high-resolution optical coherence tomography (HR-OCT). METHODS: A 78-year-old man with whorled corneal epithelial opacities in the right eye was referred for evaluation of ocular surface squamous neoplasia. Clinical evaluation, photos, and HR-OCT images of involved cornea were obtained and scrapings of the affected cornea were sent for histopathologic analysis. RESULTS: Clinically the patient presented with a opalescent whirling epithelium in a linear pattern encroaching on the visual axis. HR-OCT showed normal thickness epithelial hyperreflectivity of involved cornea without stromal involvement, along with sharply demarcated borders of unaffected tissue. Histopathologic findings demonstrated vacuolated PAS-positive cells throughout the epithelial layers consistent with LECD. CONCLUSIONS: HR-OCT was able to provide useful information to rule out ocular surface squamous neoplasia, and confirm the clinical impression of LECD at the time of clinical examination. HR-OCT shows promise as an adjunctive diagnostic tool for ocular surface lesions and pathologies