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Готові списки джерел за темами / Glaucome – Diagnostic

Добірка наукової літератури з теми "Glaucome – Diagnostic"

Автор: Grafiati

Опубліковано: 23 вересня 2022

Оновлено: 28 вересня 2022

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Статті в журналах з теми "Glaucome – Diagnostic":

1

Bresson, H., X. Zanlonghi, S. Bodet, J. P. Moisan, and F. Gerson. "473 Le glaucome : bases moléculaires et diagnostic génétique en France." Journal Français d'Ophtalmologie 28 (March 2005): 282. http://dx.doi.org/10.1016/s0181-5512(05)73593-2.

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2

Perossini, M., M. Romagnoli, T. Perossini, M. Figus, S. Benedetti, L. Corucci, and M. Nardi. "279 Le diagnostic précoce du glaucome : comparaison entre différentes techniques." Journal Français d'Ophtalmologie 28 (March 2005): 228–29. http://dx.doi.org/10.1016/s0181-5512(05)74676-3.

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3

Wroten, Chris. "Nouveautés et thérapies ´émergentes pour le glaucome." Canadian Journal of Optometry 80, no. 2 (June 1, 2018): 55–59. http://dx.doi.org/10.15353/cjo.80.271.

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On ne sait au juste quand la neuropathie optique progressive qu’est le glaucome a été découverte, mais elle est décrite dans la documentation médicale depuis les temps anciens. Hippocrate a évoqué la c´écité des personnes âgées qu’il a appelée « glaykoseis ». Bien plus tard, un ophtalmologue anglais, Richard Banister,a été le premier à constater un rapport de corrélation avec une pression intraoculaire (PIO) élevée. L’invention de l’ophtalmoscope par Hermann von Helmholtz au milieu des années 1800 a permis une première visualisation in vivo des changements glaucomateux du nerf optique et, en 1862, Franciscus Donders a inventé le terme « Glaukoma simplex » pour décrire la cécité résultant d’une PIO élevée. Peu après, l’invention du tonomètre, le développement de la périmétrie et l’utilisation de la cocaïne comme anesthésique ont fait progresser le diagnostic du glaucome.

4

Biton, C., J. P. Lemoal, J. P. Djoumegan, T. Khuc, and M. Bonsch. "510 Diagnostic échographique anténatal d’un glaucome congénital bilatéral : à propos d’un cas." Journal Français d'Ophtalmologie 28 (March 2005): 291. http://dx.doi.org/10.1016/s0181-5512(05)73630-5.

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5

Promelle, V., C. Iscar, M. Grenot, C. Gondry-Jouet, and S. Milazzo. "Les anomalies congénitales de la papille : un diagnostic différentiel du glaucome congénital." Journal Français d'Ophtalmologie 40, no. 1 (January 2017): e35-e36. http://dx.doi.org/10.1016/j.jfo.2016.08.014.

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6

Bohere, E., N. Franquet, F. Delanoy, A. Scheffer, and G. Laverdure. "504 Intérêt de l’imagerie cérébrale dans le diagnostic de glaucome à pression normale." Journal Français d'Ophtalmologie 32 (April 2009): 1S155. http://dx.doi.org/10.1016/s0181-5512(09)73628-9.

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7

Cuvier, Marion. "Examens complémentaires dans le cadre d’un diagnostic de glaucome : Mme L., une configuration particulière." Revue Francophone d'Orthoptie 6, no. 3 (July 2013): 114–18. http://dx.doi.org/10.1016/j.rfo.2013.08.001.

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8

Almárcegui Lafita, C., J. Fernandez Tirado, B. Melcon Sanchez Friera, P. Uclés Moreno, JR Valdizán Usón, and FM Honrubia López. "Étude des composants de l'électrorétinogramme par inversion de damier dans le diagnostic précoce du glaucome." Neurophysiologie Clinique/Clinical Neurophysiology 27, no. 2 (April 1997): 109–15. http://dx.doi.org/10.1016/s0987-7053(97)85663-8.

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9

Rixon, Andrew J., Rebecca A. Wenig, and Brittany N. Rigdon. "Un cas de glaucome à angle ouvert consécutif au syndrome de Posner-Schlossman." Canadian Journal of Optometry 81, no. 3 (September 4, 2019): 39–48. http://dx.doi.org/10.15353/cjo.v81i3.1561.

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Cette observation clinique présente le diagnostic et la prise en charge appropriés du syndrome de Posner-Schlossman (SPS) et de ses séquelles possibles. Le SPS se caractérise par des poussées unilatérales et récurrentes de pression intraoculaire fortement accrue. Bien que l’étiologie et la pathophysiologie de cette maladie chronique demeurent incertaines, sa durée est directement corrélée au risque de développer un glaucome secondaire à angle ouvert. Le patient et l’optométriste responsable doivent être conscients de la nécessité d’une intervention en temps opportun pendant les poussées aiguës, ainsi que du respect des soins longitudinaux pour préserver la fonction et la qualité de vie. Cette observation clinique et cet examen de cas soulignent l’impact de cette maladie.

10

Gheck, L., P. Koskas, S. N’ghiem-Buffet, and G. Chaine. "523 Apports de l’échographie Doppler couleur orbitaire dans le diagnostic étiologique d’un glaucome néovasculaire : à propos d’un cas." Journal Français d'Ophtalmologie 28 (March 2005): 294. http://dx.doi.org/10.1016/s0181-5512(05)73643-3.

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Більше джерел

Дисертації з теми "Glaucome – Diagnostic":

1

Rami, Sabrina. "Application de la méthode de Delange au diagnostic précoce du glaucome /." [S.l.] : [s.n.], 1998. http://library.epfl.ch/theses/?nr=1853.

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2

Sentenac-Mourou, Hélène. "Contribution au diagnostic précoce des hypertonies oculaires primitives par l'exploration de la fonction colorée." Bordeaux 2, 1992. http://www.theses.fr/1992BOR2M155.

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3

Mvoulana, Amed. "Vers un ophtalmologiste "augmenté" : analyse d'images rétiniennes pour l'aide au diagnostic précoce du glaucome." Thesis, Université Gustave Eiffel, 2022. http://www.theses.fr/2022UEFL2007.

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Les pathologies oculaires sont au cœur d'enjeux majeurs de santé publique. L'une d’elles, le glaucome, nécessite un dépistage précoce pour garantir le traitement efficace des patients atteints, et prévenir de déficiences visuelles irréversibles. L'avènement des approches dites de vision par ordinateur et d'apprentissage profond est à l'origine d'un changement de paradigme dans le domaine de l'ophtalmologie, vecteurs d'appui sans précédent dans les choix diagnostiques et thérapeutiques. Dans cette thèse, nous proposons de nouvelles méthodes pour le développement de systèmes intelligents dédiés au dépistage précoce de glaucome sur des images de la rétine. Nous visons notamment le déploiement de systèmes mobiles intégrant des dispositifs d'acquisition portables, pour le dépistage de proximité et/ou itinérant.Dans un premier temps, nous proposons une méthode permettant l'analyse de la tête du nerf optique (communément appelée papille), région caractérisée par un changement topographique en présence de glaucome. S’appuyant sur un algorithme précis de segmentation des structures de la papille, notamment du disque optique et de l’excavation (cup) en son sein, la méthode extrait des mesures cliniques pertinentes comme le ratio cup-disque, les secteurs inférieur-supérieur-nasal-temporal (ISNT) et l'aire de l'anneau neuro-rétinien. Un protocole clinique basé sur des références en ophtalmologie permet alors de dépister les cas glaucomateux, et donner des indications sur les stades de développement de la neuropathie (glaucome précoce, modéré ou avancé). Bien que très précise dans le dépistage, avec un taux de performance de 94% sur la base d'évaluation (DRISHTI-GS1), cette méthode a permis de mettre en lumière la nécessité d’améliorer la capacité de généralisation de l’outil, notamment en présence de papilles glaucomateuses sans excavation (faux négatifs) ou de larges papilles saines (faux positifs). Dans un deuxième temps, nous proposons une méthode basée sur des algorithmes d’apprentissage profond, permettant une interprétation automatique des traits caractéristiques de rétines saines ou glaucomateuses. Ce travail exploite des réseaux de neurones convolutionnels de l’état de l’art (VGG-16, ResNet50, Inception-v3, MobileNet et DenseNet121), et propose une méthode d'apprentissage par transfert efficace pour adapter ces réseaux à la tâche de dépistage de la pathologie. Ces modèles atteignent une AUC de plus de 0.97, toutefois, cette étude comparative a permis de déceler les besoins nécessaires au développement de modèles performants, en vue d'un déploiement en condition clinique : 1) une base d’images rétiniennes consistante en termes de taille, d'équilibre inter-classe, de fiabilité diagnostique et de variabilité clinique, 2) des modèles interprétables et explicables, permettant aux spécialistes de comprendre et discuter le résultat de dépistage. Dans ce sens, nous proposons dans un troisième temps une méthode exploitant les percées récentes de l’apprentissage semi-supervisé, pour la génération d’images rétiniennes synthétiques. L’algorithme proposé, BAGAN (pour Balancing GAN), permet de produire à partir d’une base d’images de référence (REFUGE), une base rétinienne comblant le déséquilibre inter-classes potentiellement responsable de biais diagnostiques, tout en répondant aux critères de qualité d’image et de diversité clinique. Nous avons démontré la pertinence d’une telle base dans le développement d’algorithmes semi-supervisés pour le dépistage du glaucome.Enfin, une toute nouvelle interface, disponible sur plateforme de bureau et mobile, a été conçue à destination des ophtalmologistes et professionnels de santé. Ludique et intuitive, elle intègre différentes fonctionnalités basées sur les algorithmes développées, et permet un dépistage en temps réel pour contribuer à l'amélioration de la prise en charge en santé oculaire
Ocular diseases are at the core of major public health issues. One of them, glaucoma, requires early screening to ensure effective treatment of affected patients, and prevent irreversible visual damages. The advent of so-called computer vision and deep learning approaches has led to a paradigm shift in the field of ophthalmology, providing unprecedented support in diagnostic and therapeutic choices. In this thesis, we propose new methods for the development of intelligent systems dedicated to the early detection of glaucoma from retinal images. In particular, we aim at deploying of mobile-based computer-aided diagnosis systems, for remote screening. Firstly, we proposed a method aiming at analyzing the optic nerve head, featured by morphological changes in the presence of glaucoma. Based on a precise algorithm for segmenting the structures of the optic disc and the cup within it, the method extracts clinically relevant measures such as the cup-to-disc ratio, the inferior-superior-nasal-temporal (ISNT) sectors and the neuroretinal rim area. A clinical protocol based on ophthalmic references is drawn to screen for glaucoma, and give indications about the stages of development of the neuropathy (early, moderate or advanced glaucoma). Although very accurate screening, with a performance rate of 94% on the evaluation base (DRISHTI-GS1), this method has highlighted the need to improve generalizability, particularly in the presence of glaucomatous nerve heads without excavation (false negatives) or large healthy nerve heads (false positives). Secondly, we proposed a method based on deep learning algorithms, allowing an automated interpretation of healthy or glaucomatous retinas. This work exploits state-of-the-art convolutional neural networks (VGG-16, ResNet50, Inception-v3, MobileNet and DenseNet121), and proposes an efficient transfer learning method to adapt these networks to the glaucoma screening. These models achieve an AUC of more than 0.97, however, this comparative study has identified the needs for developing efficient models for deployment in clinical conditions: 1) a consistent retinal image dataset in terms of size, inter-class balance, diagnostic reliability and clinical variability, 2) interpretable and explainable models, allowing specialists to understand and discuss the screening result.In this sense, we propose in a third step a method exploiting recent advances in semi-supervised learning, for the generation of synthetic retinal images. The proposed algorithm, BAGAN (for Balancing GAN), allows to produce from a reference image dataset (REFUGE), a new dataset filling the inter-class imbalance potentially responsible for diagnostic bias, while meeting the criteria of image quality and clinical diversity. We have demonstrated the relevance of such dataset in the further development of semi-supervised diagnosis algorithms. Finally, a brand new interface, available on desktop and mobile platforms, has been designed for ophthalmologists and health professionals. Smart and intuitive, it integrates various functionalities based on the developed algorithms, and allows real-time screening to contribute to the improvement of eye health care

4

ROULEAU, JACQUES. "Systeme expert applique au diagnostic et au traitement du glaucome primitif a angle ouvert." Clermont-Ferrand 1, 1989. http://www.theses.fr/1989CLF13803.

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5

BOUSSION, BERTRAND. "Le flicker test : une nouvelle methode de diagnostic precoce dans le glaucome primitif a angle ouvert." Angers, 1991. http://www.theses.fr/1991ANGE1086.

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6

Sousa, Jefferson Alves de. "Diagnóstico de glaucoma em retinografias utilizando funções geoestatística." Universidade Federal do Maranhão, 2017. http://tedebc.ufma.br:8080/jspui/handle/tede/1536.

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Glaucoma is one of the diseases that mopstly causes blindness, according to estimates by the World Health Organization (WHO). The Brazilian Council of Ophthalmology (CBO) estimates that in Brazil there are 985 thousand glaucoma patients with more than 40 years of age. The use of computer aided detection and diagnosis systems (CAD - Computer Aided Detection and CADx - Computer Aided Diagnosis) has contributed to increase the chances of detection and correct diagnoses. They provide a second opinion, assisting the experts in making decisions about the treatment of glaucoma. The main objective of this work is to present a method for automatic diagnosis of glaucoma in retinography images using texture characteristics. The Local Binary Pattern is used to generate a representation of the texture patterns of the image. The geostatistical functions, semivariogram, semimagram, covariogram and correlogram, are used as texture extractors. With the generated characteristics, a step is made to select the best classification model using the genetic algorithm. Then sorting is performed using the Support Vector Machine. The best result was an accuracy of 91%, sensitivity of 95% and specificity of 88%, proving that the characteristics generated by the geostatistical functions for texture extraction generate a satisfactory discriminant set.
O glaucoma e uma das doenças que mais causam cegueira em todo o mundo segundo estimativa da Organização Mundial da Saúde (OMS). O Conselho Brasileiro de Oftalmologia (CBO) estima que no Brasil existam 985 mil portadores de glaucoma com mais de 40 anos de idade. A utilização de sistemas de detecção e diagnóstico auxiliados por computador (CAD - Computer Aided Detection e CADx -Computer Aided Diagnosis) tem contribuído para aumentar as chances de detecção e diagnósticos corretos, que proporcionam, uma opinião preliminar, auxiliando os especialistas na tomada de decisões sobre o tratamento do glaucoma. O principal objetivo deste trabalho e apresentar um método para diagnóstico automático de glaucoma em imagens de retinografia utilizando características de textura. Neste trabalho, o Local Binary Pattern é usado para gerar uma representação do padrões de textura da imagem. As funções geoestatísticas, semivariograma, semimadograma, covariograma e correlograma, sao utilizadas como extratores de textura. Com as características geradas e realizada uma etapa para selecionar o melhor modelo de classificação utilizando o algoritmo genético. Em seguida é realizada a classificação usando a Maquina de Vetores de Suporte. O método apresentou como melhor resultado uma acurácia de 91%, sensibilidade de 95% e especificidade de 88%, comprovando que as características geradas pelas funções geoestatísticas para extração de textura geram um conjunto discriminante satisfatório.

7

Pascal, Lucas. "Optimization of deep multi-task networks." Thesis, Sorbonne université, 2021. http://www.theses.fr/2021SORUS535.

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L'apprentissage multi-tâches est un paradigme d'apprentissage impliquant l’optimisation de paramètres par rapport à plusieurs tâches simultanément. En apprenant plusieurs tâches liées, un modèle d'apprentissage dispose d'un ensemble d'informations plus complet concernant le domaine dont les tâches sont issues, lui permettant ainsi de construire un meilleur ensemble d’hypothèse sur ce domaine. Cependant, en pratique, les gains de performance obtenus par les réseaux multi-tâches sont loin d'être systématiques. Il arrive au contraire que ces réseaux subissent une perte de performance liée à des phénomènes d’interférences entre les différentes tâches. Cette thèse traite du problème d'interférences en apprentissage multi-tâches, afin d'améliorer les capacités de généralisation des réseaux de neurones profonds
Multi-task learning (MTL) is a learning paradigm involving the joint optimization of parameters with respect to multiple tasks. By learning multiple related tasks, a learner receives more complete and complementary information on the input domain from which the tasks are issued. This allows to gain better understanding of the domain by building a more accurate set of assumptions of it. However, in practice, the broader use of MTL is hindered by the lack of consistent performance gains observed by deep multi-task networks. It is often the case that deep MTL networks suffer from performance degradation caused by task interference. This thesis addresses the problem of task interference in Multi-Task learning, in order to improve the generalization capabilities of deep neural networks

8

Denniss, Jonathan. "Diagnostic imaging and the structure-function relationship in glaucoma." Thesis, University of Manchester, 2010. https://www.research.manchester.ac.uk/portal/en/theses/diagnostic-imaging-and-the-structurefunction-relationship-in-glaucoma(24b94e53-d0b9-4437-a639-8ea739049d22).html.

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This thesis describes a series of investigations into the use of optic nerve head (ONH) imaging in primary open-angle glaucoma (POAG), and its relation to visual function. Accurate diagnosis is a key issue in POAG, particularly the difficult task of separating those with early disease from those healthy individuals who display signs of POAG. The purpose of this work is to improve diagnostic methods in glaucoma through use of ONH imaging and its relationship with visual field (VF) loss. First, the performance of a group of expert clinicians evaluating ONH photographs for glaucomatous damage was investigated. The results showed that even when their assessments are combined discrimination between eyes with and without POAG (based on VF loss) is far from perfect, highlighting the need for improvements in diagnosis. The possibility of combining structural and functional data to aid diagnosis was then considered. This requires VF loss and ONH damage to be strongly topographically related. The strength of this relationship was evaluated in 185 patients with POAG. 10,000 computer-generated maps between the ONH and VF were tested and the topographic relationship measured with each of these was compared to that using a published structure-based map. The weak topographic relationships found suggest that the application of these maps to individual patients is limited with current measures. The next chapter describes how a multispectral imaging (MSI, also called hyperspectral imaging) system was set-up for spatial evaluation of ONH oxygenation using a Beer-Lambert law model. Test-retest repeatability was tested and found to be acceptable for the purposes of the following studies. The MSI system was then used for an investigation of the relationship between ONH oxygenation and VF loss. 33 eyes of 18 patients underwent VF testing, MSI and HRT3 imaging. Superior-inferior asymmetries in VF sensitivity were compared to superior-inferior asymmetries in ONH oxygenation measured by MSI and in neuroretinal rim (NRR) area measured by HRT3. This way we take advantage of the typical progression of POAG and each eye acts as its own reference, negating the effect of a wide normal range and overlap between health and disease. This study found, for the first time, a strong association between ONH oxygenation and VF sensitivity. A re-analysis of the 33 ONH oxygenation maps was then performed to assess oxygenation only in the area of the NRR as defined by the HRT. Superior-inferior asymmetries in NRR oxygenation were then compared to superior-inferior asymmetries in VF loss, and the associations found were similarly strong. This study shows that MSI is capable of detecting areas of NRR deemed healthy tissue by structural imaging techniques, which are in fact poorly oxygenated and associated with VF defects. These findings show that NRR oxygenation measured by MSI is strongly related to VF loss. This important information complements existing technologies and may aid in the future diagnosis and management of patients with POAG.

9

Lee, Simon. "Visual monitoring of glaucoma." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.291080.

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10

Silva, Leopoldo Magacho dos Santos. "Avaliação de parametros estruturais no diagnostico do glaucoma." [s.n.], 2004. http://repositorio.unicamp.br/jspui/handle/REPOSIP/310035.

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Orientadores: Vital Paulino Costa, Ana Maria Marcondes
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Ciencias Medicas
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Resumo: Objetivo: Avaliar a Sensibilidade e Especificidade de parâmetros estruturais (topografia de disco óptico e análise da camada de fibras nervosas da retina) no diagnóstico do glaucoma. Métodos: Pacientes com glaucoma primário de ângulo aberto foram selecionados do ambulatório de glaucoma da Unicamp. Indivíduos normais foram recrutados junto a voluntários dentro da equipe médica, amigos e parentes dos pacientes. Os participantes, após aprovação do Comitê de Ética da instituição, foram submetidos a exame oftalmológico completo, campimetria computadorizada (Humphrey Full Threshold, programa 24-2), topografia de disco óptico com o TOPSS e análise da camada de fibras nervosas da retina por meio da polarimetria de varredura a laser (GDx, versão 1.0.12). Curvas ROC foram criadas para se estabelecer novos pontos de corte para cada parâmetro individual de ambos os instrumentos. Em seguida, a análise de regressão multivariada foi empregada com parâmetros da topografia de disco óptico e polarimetria de varredura a laser separados e em conjunto para obter uma melhor relação sensibilidade/especificidade (Se/Es) no diagnóstico do glaucoma. Resultados: Cento e doze indivíduos com glaucoma e 88 normais foram incluídos. Os parâmetros individuais da polarimetria de varredura a laser com melhor capacidade em diferenciar olhos normais de glaucomatosos foram: The Number (Se: 79,5%, Es: 81,8%, área abaixo da curva ROC - aROC: 0,870), Maximum Modulation (Se: 83,0%, Es: 76,1%, aROC: 0,842) e Ellipse Modulation (Se: 65,2%, Es: 88,6%, aROC: 0,831), enquanto Average Disc Diameter (Se: 64%, Sp: 89%, aROC: 0.824), Total Disc Area (Se: 85%, Sp: 66%, aROC: 0.802) e Cup Area (Se: 69%, Sp: 85%, aROC: 0.797) foram os melhores parâmetros individuais da topografia de disco óptico. Entretanto, a análise discriminante apresentou melhores resultados que os parâmetros individuais, tanto para a polarimetria de varredura a laser (Se: 87,5%, Es: 86,4%, aROC: 0,900), topografia de disco óptico (Se: 90%, Sp: 81%, aROC: 0,910), quanto para a combinação de parâmetros derivados de ambos os instrumentos (Se: 93%, Es: 91%, aROC: 0,970). Conclusão: Parâmetros estruturais, avaliados pela topografia de disco óptico e pela polarimetria de varredura a laser apresentam boa capacidade na diferenciação entre olhos normais e glaucomatosos. Entretanto, os melhores resultados são obtidos ao combiná-los em uma função linear discriminante com parâmetros derivados de ambos os instrumentos
Abstract: Purpose: To test the ability of structural parameters (as measured by the Scanning Laser Polarimetry and Confocal Scanning Laser Ophthalmoscopy) to discriminate between normal and glaucomatous eyes. Methods: After approval of the Ethics Committee of the University of Campinas, primary open-angle glaucoma patients were selected from the glaucoma service. Normal individuals were recruited from volunteers among the medical staff, university members, family and friends of patients. All individuals underwent a thorough ophthalmic evaluation, a 24-2 full threshold Humphrey visual field, Scanning Laser Polarimetry with the GDx and Confocal Scanning Laser Ophthalmoscopy with the TOPSS. Cut-off points were selected and ROC curves were created for each individual Confocal Scanning Laser Ophthalmoscopy and Scanning Laser Polarimetry parameters. Finally, multivariate discriminant formulas were developed in order to achieve a better sensitivity (Se)/specificity (Sp) ratio for the diagnosis of glaucoma, initially separately for each device, and then combining parameters from Confocal Scanning Laser Ophthalmoscopy and Scanning Laser Polarimetry. Results: One-hundred and twelve patients with primary open-angle glaucoma and 88 normal individuals were enrolled in the study. The best Scanning Laser Polarimetry parameters in differentiating normal individuals from glaucoma patients were: The Number (Se: 79,5%, Es: 81,8%, area under the ROC curve- aROC: 0,870), Maximum Modulation (Se: 83,0%, Es: 76,1%, aROC: 0,842) and Ellipse Modulation (Se: 65,2%, Es: 88,6%, aROC: 0,831), while the best Confocal Scanning Laser Ophthalmoscopy individual parameters were: Average Disc Diameter (Se: 64%, Sp: 89%, aROC: 0,824), Total Disc Area (Se: 85%, Sp: 66%, aROC: 0,802) and Cup Area (Se: 69%, Sp: 85%, aROC: 0,797). However, the multivariate analysis resulted in better results for the Scanning Laser Polarimetry (Se: 87,5%, Es: 86,4%, aROC: 0,900), Confocal Scanning Laser Ophthalmoscopy (Se: 90%, Sp: 81%, aROC: 0,910), and for the combination of parameters from both devices (Se: 93%, Es: 91%, aROC: 0,970). Conclusion: Structural parameters, as measured by the Confocal Scanning Laser Ophthalmoscopy and Scanning Laser Polarimetry have good ability to differentiate normal individuals from glaucoma patients. However, better results are obtained combining parameters from both devices in a multivariate discriminant formula
Doutorado
Oftalmologia
Doutor em Ciências Médicas

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Книги з теми "Glaucome – Diagnostic":

1

Salmon, John F. Glaucoma: A colour manual of diagnosis and treatment. 3rd ed. Oxford: Butterworth-Heinemann, 2004.

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2

Stamper, Robert L. Becker-Shaffer's diagnosis and therapy of the glaucomas. 8th ed. [Edinburgh]: Mosby/Elsevier, 2009.

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3

Becker, Bernard. Becker-Shaffer's diagnosis and therapy of the glaucomas. 6th ed. St. Louis: Mosby, 1989.

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4

Global, AIGS Consensus Meeting (2nd 2005 Ft Lauderdale Fla ). Glaucoma surgery: Open angle glaucoma : reports and consensus statements of the 2nd Global AIGS Consensus Meeting on "glaucoma surgery-open angle glaucoma". The Hague, Netherlands: Kugler Publications, 2005.

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5

Edward, Deepak P. Glaucoma. Oxford: Oxford University Press, 2012.

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6

Pfeiffer, Norbert. Glaukom: Grundlagen, Diagnostik, Therapie, Compliance. Stuttgart, Germany: Thieme, 2001.

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7

Gupta, Deepak. Glaucoma diagnosis and management. Philadelphia: Lippincott Williams & Wilkins, 2005.

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8

Ramakrishan, R. Diagnosis and management of glaucoma. Panama City, Panama: Jaypee-Highlights Medical Publishers, Inc., 2013.

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9

Elseid, Arwa Ahmed Gasm, and Alnazier Osman Mohammed Hamza. Computer-Aided Glaucoma Diagnosis System. First edition. | Boca Raton, FL : CRC Press, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780367406288.

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10

Weinreb, Robert N., Paul R. Healey, and Fotis Topouzis. Glaucoma screening: Screening for open angle glaucoma, primary angle-closure and primary angle-closure glaucoma : the 5th consensus report of the World Glaucoma Association. Amsterdam, The Netherlands: Kugler Publications, 2008.

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Частини книг з теми "Glaucome – Diagnostic":

1

Weinreb, Robert N., Christopher Bowd, Sasan Moghimi, Ali Tafreshi, Sebastian Rausch, and Linda M. Zangwill. "Ophthalmic Diagnostic Imaging: Glaucoma." In High Resolution Imaging in Microscopy and Ophthalmology, 107–34. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16638-0_5.

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2

Thakur, Sahil. "What’s the Future of Glaucoma Diagnosis and Neuroprotection." In Glaucoma, 115–23. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8457-8_9.

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3

Townsend, Kelly A., Gadi Wollstein, and Joel S. Schuman. "Future Glaucoma Instrumentation: Diagnostic and Therapeutic." In The Glaucoma Book, 995–1009. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-76700-0_90.

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4

Moghimi, Sasan, Mona SafiZadeh, Andrew Camp, and Robert N. Weinreb. "OCT and Glaucoma: Interpretation." In Diagnostics in Ocular Imaging, 579–603. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54863-6_25.

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5

Moghimi, Sasan, Mona SafiZadeh, Andrew Camp, and Robert N. Weinreb. "OCT Artifacts in Glaucoma." In Diagnostics in Ocular Imaging, 631–63. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54863-6_27.

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6

Tello, Celso, Jeffrey M. Liebmann, and Robert Ritch. "New Concepts in the Diagnosis of Angle-Closure Glaucoma: The Role of Ultrasound Biomicroscopy." In Glaucoma, 93–104. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-18633-2_6.

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7

Moghimi, Sasan, Mona SafiZadeh, Andrew Camp, and Robert N. Weinreb. "OCT and Glaucoma: Case Review." In Diagnostics in Ocular Imaging, 605–30. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54863-6_26.

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8

Leonard, Kevin C., and Cindy M. L. Hutnik. "Using Electroretinography for Glaucoma Diagnosis." In The Glaucoma Book, 265–67. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-76700-0_24.

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9

Hangai, Masanori. "Glaucoma Diagnosis in Myopic Eyes." In Myopia and Glaucoma, 25–51. Tokyo: Springer Japan, 2015. http://dx.doi.org/10.1007/978-4-431-55672-5_3.

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10

Ichhpujani, Parul. "Recent Advances in Glaucoma Diagnostics." In Current Advances in Ophthalmic Technology, 69–81. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9795-0_4.

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Тези доповідей конференцій з теми "Glaucome – Diagnostic":

1

Girard, Michaël J. A., Lyn Zimmo, Edward T. White, Jean Martial Mari, C. Ross Ethier, and Nicholas G. Strouthidis. "Towards a Biomechanically-Based Diagnosis for Glaucoma: In Vivo Deformation Mapping of the Human Optic Nerve Head." In ASME 2012 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/sbc2012-80557.

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Анотація:

Glaucoma is the most common cause of irreversible blindness. It is associated with a progressive loss of cells within the optic nerve head (ONH) at the back of the eye. Glaucoma remains incurable and its exact causes are not well understood. It was once thought to occur only in eyes with elevated pressure (i.e., intraocular pressure or IOP) and to date, lowering IOP is the only clinical treatment proven to be beneficial for slowing the progression of glaucoma. However, the success rate of such therapy is only 50%. Multiple lines of evidence now indicate that IOP is not the only important risk factor in the disease. For instance, while some patients develop glaucoma at elevated IOP (high-tension glaucoma), some develop glaucoma at normal IOP levels (normal-tension glaucoma), and some others with elevated IOP do not develop glaucoma at all.

2

Thangaraj, Vigneswaran, and V. Natarajan. "Glaucoma diagnosis using support vector machine." In 2017 International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2017. http://dx.doi.org/10.1109/iccons.2017.8250750.

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3

Singh, Amitojdeep, Sourya Sengupta, and Vasudevan Lakshminarayanan. "Glaucoma diagnosis using transfer learning methods." In Applications of Machine Learning, edited by Michael E. Zelinski, Tarek M. Taha, Jonathan Howe, Abdul A. Awwal, and Khan M. Iftekharuddin. SPIE, 2019. http://dx.doi.org/10.1117/12.2529429.

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4

Vlad, Simona, Sorina Demea, Horea Demea, and Rodica Holonec. "Neural network classifier for glaucoma diagnosis." In 2015 E-Health and Bioengineering Conference (EHB). IEEE, 2015. http://dx.doi.org/10.1109/ehb.2015.7391596.

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5

Borwankar, Saumya, Raima Sen, and Bhavin Kakani. "Improved Glaucoma Diagnosis Using Deep Learning." In 2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2020. http://dx.doi.org/10.1109/conecct50063.2020.9198524.

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6

Liu, J., F. S. Yin, D. W. K. Wong, Z. Zhang, N. M. Tan, C. Y. Cheung, M. Baskaran, T. Aung, and T. Y. Wong. "Automatic glaucoma diagnosis from fundus image." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6090916.

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7

Jun Cheng, Jiang Liu, Damon Wing Kee Wong, Ngan Meng Tan, Beng Hai Lee, Carol Cheung, M. Baskaran, Tien Yin Wong, and Tin Aung. "Focal edge association to glaucoma diagnosis." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6091111.

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8

Wang, Jingwen, Yuguang Yan, Yanwu Xu, Wei Zhao, Huaqing Min, Mingkui Tan, and Jiang Liu. "Conditional Adversarial Transfer for Glaucoma Diagnosis." In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8857308.

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9

Kang, Hong, Xiaoxing Li, and Xiu Su. "Cup-disc and retinal nerve fiber layer features fusion for diagnosis glaucoma." In Computer-Aided Diagnosis, edited by Horst K. Hahn and Maciej A. Mazurowski. SPIE, 2020. http://dx.doi.org/10.1117/12.2548546.

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10

Stolfi, Carolyn, and Jenn S. Rossmann. "Biomechanics of Glaucoma: A Parametric Study of Flow in Schlemm’s Canal." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-12355.

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Анотація:

Glaucoma is one of the most common causes of blindness, affecting approximately seventy million people. Glaucoma is typically caused by high intraocular pressures due to increased outflow resistance, which is primarily concentrated within the trabeculae meshwork and the canal of Schlemm. Debris within trabecular spaces can complicate and limit formation and reabsorption of aqueous humor, leading to elevated interocular pressures. In this study, the biomechanics of Primary Open-Angle Glaucoma are investigated. Computational modeling in physiologically realistic geometries is performed to examine the relationship between intraocular pressure and downstream trabecular and canal resistance. The governing equations for fluid flow are solved, and the influence of such factors as tissue porosity is evaluated. Increased understanding of the biomechanics of glaucoma can improve diagnosis and treatment of this disease.