\u3cem\u3eIn vivo\u3c/em\u3e Imaging of Human Retinal Microvasculature Using Adaptive Optics Scanning Light Ophthalmoscope Fluorescein Angiography

The adaptive optics scanning light ophthalmoscope (AOSLO) allows visualization of microscopic structures of the human retina in vivo. In this work, we demonstrate its application in combination with oral and intravenous (IV) fluorescein angiography (FA) to the in vivo visualization of the human retinal microvasculature. Ten healthy subjects ages 20 to 38 years were imaged using oral (7 and/or 20 mg/kg) and/or IV (500 mg) fluorescein. In agreement with current literature, there were no adverse effects among the patients receiving oral fluorescein while one patient receiving IV fluorescein experienced some nausea and heaving. We determined that all retinal capillary beds can be imaged using clinically accepted fluorescein dosages and safe light levels according to the ANSI Z136.1-2000 maximum permissible exposure. As expected, the 20 mg/kg oral dose showed higher image intensity for a longer period of time than did the 7 mg/kg oral and the 500 mg IV doses. The increased resolution of AOSLO FA, compared to conventional FA, offers great opportunity for studying physiological and pathological vascular processes

Processing in vivo ultrasound images of the carotid artery

Carotid stenosis is a narrowing of the carotid arteries, the two major arteries that carry oxygen-rich blood from the heart to the brain. This disease is caused by a buildup of plaque (atherosclerosis) inside the artery wall that reduces blood flow to the brain. This thesis focuses on predicting whether the plaque in the carotid artery is unstable (symptomatic) or stable (asymptomatic) using ultrasound images of the carotid artery. If it is unstable it means that the plaque is going to grow, otherwise, is going to remain the same. Using a provided segmentation, a series of descriptors and a subsequent classification model has been developed to fulfil this task. We will see that between the linear regression classifier, SVC or Random Forest, SVC will give the best results. For the cross-sectional images, the descriptors that will give us the best accuracy in distinguishing the two classes will be: relative percentage stenosis, relative plaque area, wavelets and Haralick texture descriptors. The first two will be calculated on the cross-sectional segmentations and the last ones on the original cross-sectional images using segmentations as well. With this selection of features we will achieve 67% accuracy in the classification of our data.La estenosis carotídea es un estrechamiento de las arterias carótidas, las dos arterias principales que llevan la sangre rica en oxígeno del corazón al cerebro. Esta enfermedad está causada por una acumulación de placa (aterosclerosis) en el interior de la pared arterial que reduce el flujo sanguíneo al cerebro. La presente tesis se centra en predecir si la placa en la arteria carótida es inestable (sintomática) o estable (asintomática) utilizando las imágenes ecográficas de la arteria carótida. Si es inestable significa que la placa va a crecer, por otra parte, si es estable, se mantendrá igual. Mediante una segmentación que nos ha sido facilitada, se han desarrollado una serie de descriptores y un posterior modelo de clasificación para cumplir este cometido. Veremos que entre el clasificador de regresión lineal, SVC o Random Forest, SVC será el que nos dará mejores resultados. Para las imágenes transversales, los descriptores que nos darán una mayor precisión al distinguir las dos clases serán: porcentaje de estenosis relativa, área relativa de la placa, wavelets y los descriptores de textura de Haralick. Las dos primeras se calcularán sobre les segmentaciones transversales y las últimas sobre las imágenes transversales originales utilizando también las segmentaciones. Con esta selección de características se conseguirá un 67% de precisión en la clasificación de nuestros datos.L'estenosi carotídia és un estrenyiment de les artèries caròtides, les dues artèries principals que porten la sang rica en oxigen del cor al cervell. Aquesta malaltia està causada per una acumulació de placa (aterosclerosi) a l'interior de la paret arterial que redueix el flux sanguini al cervell. La tesis que es presenta es centra en predir si la placa en l'arteria caròtida és inestable (simptomàtica) o estable (asimptomàtica) utilitzant les imatges ecogràfiques de l'arteria caròtida. Si és inestable significa que la placa creixerà, d'altra banda, si és estable, romandrà igual. Mitjançant una segmentació que se'ns ha facilitat, s'han desenvolupat una sèrie de descriptors i un posterior model de classificació per complir aquesta comesa. Veurem que entre el classificador de regressió lineal, SVC o Random Forest, SVC serà amb el que obtindrem millors resultats. Per les imatges transversals, els descriptors que ens donaran una major precisió al distingir les dos classes seran: percentatge d'estenosis relativa, àrea relativa de la placa, wavelets i els descriptors de textura de Haralick. Les dues primeres es calcularan sobre les segmentacions transversals i les últimes sobre les imatges transversals originals utilitzant també les segmentacions. Amb aquesta selecció de característiques s'aconseguirà un 67% de precisió en la classificació de les nostres dades

Automatic Wide Field Registration and Mosaicking of OCTA Images Using Vascularity Information

[Abstract] Optical Coherence Tomography Angiography (OCTA) constitutes a novel ophthalmological image modality that is characterized for being a non-invasive capture technique that allows a profound analysis of the vascular characteristics of the eye fundus. Given the restricted field of view of the eye fundus that offers each scan, the specialists frequently capture several complementary images that may be simultaneously analyzed to offer a complete and accurate diagnosis of the patient. In this work, we propose a fully automatic method to register complementary OCTA images and provide compositions for the same patient, generating a wide field of representation that allows a simpler and more direct analysis than the traditional tedious manual procedures. To achieve this, we based our proposal in a robust combination of representative features that are filtered by an accurate identification of the main retinal vasculature. This way, given the characteristic high irregularity in the fundus of the OCTA images, we avoid many variable areas that may interfere in the registration process, restricting the analysis to the most representative and stable structure of this image modality, the main retinal vasculature. In particular, we use Speeded-Up Robust Features (SURF) algorithm to extract representative features in the main vascular region that is extracted using a method that combines the analysis of the Hessian matrix followed by an hysteresis threshold process. Then, using a K-NN model, we perform the registration of the resulting features from the different OCTA images to be analyzed. Finally, the Random sample consensus (RANSAC) method is exploited to produce the final target mosaic. The proposed method presented satisfactory results in the validation experiments, with accurate values for the MSE index of 1.2566 and 1.6725 pixels for the registration of paired images an mosaics, respectively.Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2016-047This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the DTS18/00136 research projects and by the Ministerio de Economía y Competitividad, Government of Spain through the DPI2015-69948-R research project. Also, this work has received financial support from the European Union (European Regional Development Fund - ERDF) and the Xunta de Galicia, Centro singular de investigación de Galicia accreditation 2016-2019, Ref. ED431G/01; and Grupos de Referencia Competitiva, Ref. ED431C 2016-047

Glaucomatous Macular Vasculature: A Quantitative Analysis

Background: The aim of this study was to evaluate the characteristics of the macular vessel density (VD) and the foveal avascular zone (FAZ) in glaucoma quantitatively using the optical coherence tomography angiography (OCT-A). Methods: Twenty-five eyes of 13 patients with primary open angle glaucoma (POAG) and 12 eyes of 6 healthy participants were enrolled retrospectively. Functional visual field (VF) and structural Spectral-Domain optical coherence tomography (SD-OCT) Retinal Nerve Fiber Layer Thickness (RNFLT) were assessed in all participants. OCT-A was performed on a fovea centered, 15x10 degrees, macular region. OCT-A scans were processed with MATLAB software and automatically graded to define FAZ parameters. The parafoveal VD in the superficial and deep retinal vascular plexus (SVP and DVP) was analyzed by quadrant and circular segmented zones. Results: Foveal Avascular Zone -Major Axis Length (p=0.02), Area (p=0.04), Equivalent Diameter (p=0.04) and Perimeter (p=0.04) were significantly larger in glaucoma than the control group. Regarding SVP and DVP, the average macular total VD were lower in glaucoma patients compared to the control group (p<0.01; p<0.01). Additionally, the inner circular region (p=0.04; p<0.01 respectively for SVP and DVP) and all quadrants except for North had a lower VD in glaucoma group compared to the control group. Assessment of the total VD successfully predicted RNFLT (p<0.001) and was significantly associated with the probability of glaucoma (p=0.009). Conclusion: OCT-A parameters, namely the FAZ morphology and the macular VD, were associated with glaucomatous functional and structural changes. The macular VD showed a considerable diagnostic value. It may be a modern biomarker, representing microvascular network disruption of the macular perfusion in glaucoma