Corneal Nerve Fiber Structure, Its Role in Corneal Function, and Its Changes in Corneal Diseases

Recently, in vivo confocal microscopy is used to examine the human corneal nerve fibers morphology. Corneal nerve fiber architecture and its role are studied in healthy and pathological conditions. Corneal nerves of rats were studied by nonspecific acetylcholinesterase (NsAchE) staining. NsAchE-positive subepithelial (stromal) nerve fiber has been found to be insensitive to capsaicin. Besides, NsAchE-negative but capsaicin-sensitive subbasal nerve (leash) fibers formed thick mesh-like structure showing close interconnections and exhibit both isolectin B4- and transient receptor potential vanilloid channel 1- (TRPV1-) positive. TRPV1, TRPV3, TRPA (ankyrin) 1, and TRPM (melastatin) 8 are expressed in corneal nerve fibers. Besides the corneal nerve fibers, the expressions of TRPV (1, 3, and 4), TRPC (canonical) 4, and TRPM8 are demonstrated in the corneal epithelial cell membrane. The realization of the importance of TRP channels acting as polymodal sensors of environmental stresses has identified potential drug targets for corneal disease. The pathophysiological conditions of corneal diseases are associated with disruption of normal tissue innervation, especially capsaicin-sensitive small sensory nerve fibers. The relationships between subbasal corneal nerve fiber morphology and neurotrophic keratopathy in corneal diseases are well studied. The recommended treatment for neurotrophic keratopathy is administration of preservative free eye drops

Novel medical imaging technologies for processing epithelium and endothelium layers in corneal confocal images. Developing automated segmentation and quantification algorithms for processing sub-basal epithelium nerves and endothelial cells for early diagnosis of diabetic neuropathy in corneal confocal microscope images

Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the corneal epithelium nerve structures and the corneal endothelial cell can assist early diagnosis of this disease and other corneal diseases, which can lead to visual impairment and then to blindness. In this thesis, fully-automated segmentation and quantification algorithms for processing and analysing sub-basal epithelium nerves and endothelial cells are proposed for early diagnosis of diabetic neuropathy in Corneal Confocal Microscopy (CCM) images. Firstly, a fully automatic nerve segmentation system for corneal confocal microscope images is proposed. The performance of the proposed system is evaluated against manually traced images with an execution time of the prototype is 13 seconds. Secondly, an automatic corneal nerve registration system is proposed. The main aim of this system is to produce a new informative corneal image that contains structural and functional information. Thirdly, an automated real-time system, termed the Corneal Endothelium Analysis System (CEAS) is developed and applied for the segmentation of endothelial cells in images of human cornea obtained by In Vivo CCM. The performance of the proposed CEAS system was tested against manually traced images with an execution time of only 6 seconds per image. Finally, the results obtained from all the proposed approaches have been evaluated and validated by an expert advisory board from two institutes, they are the Division of Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar and the Manchester Royal Eye Hospital, Centre for Endocrinology and Diabetes, UK

Caracterização de patologias da pele por ultrassons

A pele constitui a primeira barreira física que o corpo humano dispõe para proteção, sendo importante manter as suas características. Para a sua avaliação e diagnóstico, a técnica por ultrassons, nomeadamente a ecografia, apresenta-se como uma abordagem com utilização crescente devido ao seu carácter não invasivo, não ionizante e acessível (baixo custo), quando comparado com outras técnicas de imagiologia. O principal objetivo da presente dissertação consiste no desenvolvimento de três abordagens com vista à caracterização da pele, usando tecnologia por ultrassons. Para tal foram usadas imagens ecográficas de doentes assim como imagens obtidas a partir de fantomas criados no Laboratório de Tecnologia de Materiais Elétricos e Ultrassons, do Departamento de Engenharia Electrotécnica e de Computadores, da Faculdade de Ciências e Tecnologia da Universidade de Coimbra. Duas dessas abordagens permitem a caracterização completamente automática de imagens de forma global ou recorrendo a características texturais da imagem, eliminando possíveis ambiguidades resultantes do processo de interação com utilizadores. A metodologia desenvolvida inclui mais de 400 características texturais, 5 classificadores, seletores de características e um algoritmo de fusão de classificadores. A terceira abordagem permite a classificação de imagens de fantomas a partir do uso de apenas três parâmetros acústicos, revelando a possibilidade de desenvolvimento de técnicas de caracterização, recorrendo apenas a parâmetros acústicos, tornando a técnica ainda mais acessível. O trabalho desenvolvido mostrou que os ultrassons podem ser utilizados para distinguir pele com lesão de pele sem lesão. Utilizando características texturais das imagens é possível obter um valor F-score igual a 96,3% para imagens de pele. Mostrou-se ainda, que a utilização de apenas três parâmetros acústicos extraídos dos fantomas permite a sua classificação com um F-score igual a 89,1%. Palavras-Chave: Ultrassons, Fantomas, Parâmetros Acústicos, Processamento de Imagem Médica, Algoritmos de Classificaçã