Registration of SD-OCT en-face images with color fundus photographs based on local patch matching

Registration of multi-modal retinal images is very significant to integrate information gained from different modalities for a reliable diagnosis of retinal diseases by ophthalmologists. However, accurate image registration is a challenging, we propose an algorithm for registration of summed-voxel projection images (SVPIs) with color fundus photographs (CFPs) based on local patch matching. SVPIs are evenly split into 16 local image blocks for extracting matching point pairs by searching local maximization of the similarity function. These matching point pairs are used for a coarse registration and then a search region of feature matching points is redefined for a more accurate registration. The performance of our registration algorithm is tested on a series of datasets including 3 normal eyes and 20 eyes with age-related macular degeneration. The experiment demonstrates that the proposed method can achieve accurate registration results (the average of root mean square error is 128μm)

Optical coherence tomography angiography metrics Monitor severity progression of diabetic retinopathy—3-year longitudinal study

To examine retinal vessel closure metrics and neurodegenerative changes occurring in the initial stages of nonproliferative diabetic retinopathy (NPDR) and severity progression in a three-year period. Three-year prospective longitudinal observational cohort of individuals with type 2 diabetes (T2D), one eye per person, using spectral domain-optical coherence tomography (SD-OCT) and OCT-Angiography (OCTA). Eyes were examined four times with one-year intervals. OCTA vessel density maps of the retina were used to quantify vessel closure. Thickness of the ganglion cell + inner plexiform layer (GCL + IPL) was examined to identify retinal neurodegenerative changes. Diabetic retinopathy ETDRS classification was performed using the seven-field ETDRS protocol. A total of 78 eyes/patients, aged 52 to 80 years, with T2D and ETDRS grades from 10 to 47 were followed for 3 years with annual examinations. A progressive increase in retinal vessel closure was observed. Vessel density (VD) showed higher decreases with retinopathy worsening demonstrated by step-changes in ETDRS severity scale (p < 0.001). No clear correlation was observed between neurodegenerative changes and retinopathy progression. Conclusions: Retinal vessel closure in NPDR correlates with DR severity progression. Our findings provide supporting evidence that OCTA metrics of vessel closure may be used as a surrogate for DR severity progression.info:eu-repo/semantics/publishedVersio

COMPUTER MODELING OF BREAST LESIONS AND STUDIES OF ANALYZER-BASED X-RAY IMAGING

Phase-contrast x-ray imaging is an emerging technique that promises to yield highly sensitive medical images of soft tissue, which is difficult to observe via conventional radiography given its low X-ray attenuation differences. One of these phase-contrast techniques, known as analyzer-based imaging, has demonstrated that highly detailed breast tissue images can be obtained using synchrotron radiation. However, synchrotron facilities are impractical for clinical use. This thesis introduces studies and exposure consideration towards the application of analyzer-based imaging in a clinical environment, particularly in the context of breast imaging. It also introduces a computational breast lesion model that generates randomized three-dimensional phantoms which follow realistically the characteristics observed in real lesions. Moving analyzer-based imaging to clinical application requires the consideration of photon noise, inherent from the use of a photon-limited conventional source. We summarize the statistical properties in the presence of photon noise of two popular analyzer-based imaging techniques, known as diffraction-enhanced imaging (DEI) and multiple-image radiography (MIR). The statistics for MIR have not been previously derived and are introduced in this thesis. Comparison of the resulting statistical predictions with results obtained by Monte Carlo simulation validated the analysis. An expression for the maximum-likelihood (ML) solution for analyzer-based imaging is presented as a way of minimizing the effects of photon noise in the reconstruction of the object’s absorption, refraction and ultra-small angle scattering properties, and more practical maximum-likelihood expectation-maximization (ML-EM) and maximum-a-posteriori expectation-maximization (MAP-EM) solutions are also introduced. The behavior of the ML-EM and MAP-EM solutions was compared to the results produced by the five best-known analyzer-based reconstruction methods using computer simulations. The ML-EM and MAP-EM reconstructions proved closer to the theoretical values as they do not rely on commonly known limitations and approximations introduced by the other techniques. We introduce the development and evaluation of a new computational breast lesion phantom model that can simulate either massess or microcalcifications. The proposed tool allows the generation of a large number of randomized three-dimensional breast lesion simulations following desired characteristics normally used to describe breast lesions in clinical practice. The initial motivation for the development of this new phantom model was to enable the proposed evaluations of analyzer-based imaging to be achieved. However, the model became a major focus of this thesis because it improves significantly upon those that can be found in previous literature. The proposed lesion model can be used for evaluation studies across different breast imaging techniques, as well as for training purposes, so it is our hope that it could become an important resource for the broader mammography research community. As part of the lesion modeling research, we also introduce methods to computationally modify experimental mammography and analyzer-based images of breast tissue so that they present the generated tumor simulations embedded within their parenchyma realistically. The realism of the simulated lesion images was evaluated by comparison of 83 real tumor cases observed in mammograms with 83 constructed hybrid images in which simulated tumors matching the characteristics observed in the real cases were embedded, with healthy tissue acting as background. As a quantitative comparison, extracted features describing tumor shape and density showed no statistically significant differences between real and simulated tumors. A known computational tumor classification technique based on their shape observed in mammography was implemented and showed no significant performance differences between real and simulated cases, as well as showing good correlation with previously published performance results in real tumors. To measure the realism for use in human observer studies, we conducted a reader study in which 5 experienced radiologists were asked to judge whether each of the 166 images was real or simulated by assigning a score on a 7-point scale. The results were analyzed in a multiple-reader multiple-case statistical framework. The conclusion of the study was that the readers’ accuracy in assessing whether the lesions were real or simulated was not significantly better than random chance. This thesis also incorporates a reader study to evaluate the degree to which photon-limited analyzer-based images may be effective for visualization of breast cancer features. Our motivation was to establish the x-ray intensity that would be required to make these methods feasible, the purpose being to serve as a guide in parameter selection for future design of imaging hardware. We conducted a series of observer studies that quantify the performance of analyzer-based refraction images at different noise levels for the task of identifying subtle details present in breast tumors which are relevant to clinical diagnosis. The cases shown to the readers consisted of hybrid images where simulated lesions of known characteristics were computationally embedded in real breast analyzer-based background images. The original phase-contrast data was obtained using synchrotron radiation and was later modified to simulate the noise and blurring effects produced from a photon-limited source with a 300μm aperture size, similar to those used in a laboratory environment. Results showed that the analyzer-based imaging techniques statistically outperformed conventional mammography for the given task with an average of just 128 recorded photons per pixel in background image regionsPh.D. in Electrical Engineering, December 201

Por la ciudad de Orihuela. Con el colegio de Predicadores de la dicha ciudad. En el pleito de accion Negatoria, vulgo Requesta, que siguen sobre el Censo de 5500.lib.

Copia digital. Zaragoza, 200

Informe legal y politico a la S.C.R.M. del Rey... por los Iurados de la... ciudad de Valencia, y por los insaculados para los oficios mayores...

Precede al tit. "Iesus, María..."Port. con orla tip. y esc. calc. de la ciudad de Valencia : "F. Q."Sign.: A-G

Early alterations in retinal microvasculature on swept-source optical coherence tomography angiography in acute central serous chorioretinopathy

Abstract The purpose of the study was to evaluate the retinal blood flow in patients with acute central serous chorioretinopathy (CSC) over an observational period of 1 month using swept-source optical coherence tomography (SS-OCTA), focusing especially on changes in the area of subretinal fluid (A-SRF). We correlated these findings with conventional indocyanine green angiography (ICGA). ICGA and SS-OCTA images were collected and analyzed of 12 eyes of 12 patients. The A-SRF was annotated and a qualitative analysis of choriocapillaris, the vessel density (VD) and perfusion density (PD) of the retinal superficial capillary plexus (SCP) and the deep capillary plexus (DCP) was performed in A-SRF and the unaffected remaining area (RA). The VD and PD in the DCP were statistically significantly lower in A-SRF than in the RA at baseline. (VD: p = 0.014; PD: p = 0.036). After 1 month, there was a statistically significant difference in the VD and PD of the DCP (VD: p = 0.015; PD: p = 0.014), and for the PD of the SCP between the A-SRF and the RA (p = 0.015), with lower values in the A-SRF. We found low perfused areas in choriocapillaris corresponding to hypofluorescent areas on ICGA. In conclusion there is a difference in VD and VD of the DCP in the area of SRF in acute CSC. These alterations may lead to a chronic change in the microvasculature and potentially to morphological changes

Validation of a Novel Automated Algorithm to Measure Drusen Volume and Area Using Swept Source Optical Coherence Tomography Angiography

The purpose of this study was to validate a novel automated swept source optical coherence tomography angiography (SS-OCTA) algorithm to measure elevations of the retinal pigment epithelium (RPE) in eyes with nonexudative age-related macular degeneration (neAMD). Patients with drusen were enrolled in a prospective optical coherence tomography (OCT) study and underwent both spectral domain OCT (SD-OCT) and SS-OCTA imaging at the same visit using the 6 × 6 mm scan patterns. The RPE elevation measurements (square root area and cube root volume) from the SS-OCTA algorithm were compared with the automated validated SD-OCT algorithm on the instrument. Standard deviations of drusen measurements from four repeated scans of another separate set were also calculated to evaluate the reproducibility of the SS-OCTA algorithm. A total of 53 eyes from 28 patients were scanned on both instruments. A very strong correlation was found between the measurements from the two algorithms (all r > 0.95), although the measurements of the drusen area and volume were all larger from the SS-OCTA instrument. The reproducibility of the new SS-OCTA algorithm was analyzed using a sample of 66 eyes from 43 patients. The intraclass correlation coefficient (ICC) was greater than 99% from different macular regions for both the square root area and cube root volume measurements. A novel automated SS-OCTA algorithm for the quantitative assessment of drusen was validated against the SD-OCT algorithm and was shown to be highly reproducible. This novel SS-OCTA algorithm provides a strategy to measure the area and volume of drusen to assess disease progression in neAMD

Por la Ciudad de Segorve, con el muy ilustre Duque

Sig. A-R2, S1Reclams. - Capital grav

Prediction of age-related macular degeneration disease using a sequential deep learning approach on longitudinal SD-OCT imaging biomarkers

We propose a hybrid sequential prediction model called "Deep Sequence", integrating radiomics-engineered imaging features, demographic, and visual factors, with a recursive neural network (RNN) model in the same platform to predict the risk of exudation within a future time-frame in non-exudative AMD eyes. The proposed model provides scores associated with risk of exudation in the short term (within 3 months) and long term (within 21 months), handling challenges related to variability of OCT scan characteristics and the size of the training cohort. We used a retrospective clinical trial dataset that includes 671 AMD fellow eyes with 13,954 observations before any signs of exudation for training and validation in a tenfold cross validation setting. Deep Sequence achieved high performance for the prediction of exudation within 3 months (0.96 ± 0.02 AUCROC) and within 21 months (0.97 ± 0.02 AUCROC) on cross-validation. Training the proposed model on this clinical trial dataset and testing it on an external real-world clinical dataset showed high performance for the prediction within 3-months (0.82 AUCROC) but a clear decrease in performance for the prediction within 21-months (0.68 AUCROC). While performance differences at longer time intervals may be derived from dataset differences, we believe that the high performance and generalizability achieved in short-term predictions may have a high clinical impact allowing for optimal patient follow-up, adding the possibility of more frequent, detailed screening and tailored treatments for those patients with imminent risk of exudation