Enhancing Pathological Detection and Monitoring in OCT Volumes with Limited Slices using Convolutional Neural Networks and 3D Visualization Techniques

Cursos e Congresos, C-155[Abstract] Optical Coherence Tomography (OCT) is a non-invasive imaging technique with a crucial role in the monitoring of a wide range of diseases. In order to make a good diagnosis it is essential that clinicians can observe any subtle changes that appear in the multiple ocular structures, so it is imperative that the 3D OCT volumes have good resolution in each axis. Unfortunately, there is a trade-off between image quality and the number of volume slices. In this work, we use a convolutional neural network to generate the intermediate synthetic slices of the OTC volumes and we propose a few variants of a 3D reconstruction algorithm to create visualizations that emphasize the changes present in multiple retinal structures to aid clinicians in the diagnostic processXunta de Galicia; ED431C 2020/24This research was funded by Government of Spain, Ministerio de Ciencia e Innovación y Universidades, Government of Spain, RTI2018-095894-B-I00 research project; Ministerio de Ciencia e Innovación, Government of Spain through the research projects with reference PID2019-108435RB-I00, PDC2022-133132-I00 and TED2021-131201B-I00; Consellería de Cultura, Educación e Universidade, Xunta de Galicia through the Grupos de Referencia Competitiva, grant ref. ED431C 2020/24; CITIC, as Research Center accredited by Galician University System, is funded by ”Consellería de Cultura, Educación e Universidade from Xunta de Galicia”, supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014-2020, and the remaining 20% by ”Secretaría Xeral de Universidades”, grant ref. ED431G 2019/01. Emilio López Varela acknowledges its support under FPI Grant Program through PID2019-108435RB-I00 project

Assessment of the repeatability in an automatic methodology for hyperemia grading in the bulbar conjunctiva

When the vessels of the bulbar conjunctiva get congested with blood, a characteristic red hue appears in the area. This symptom is known as hyperemia, and can be an early indicator of certain pathologies. Therefore, a prompt diagnosis is desirable in order to minimize both medical and economic repercussions. A fully automatic methodology for hyperemia grading in the bulbar conjunctiva was developed, by means of image processing and machine learning techniques. As there is a wide range of illumination, contrast, and focus issues in the images that specialists use to perform the grading, a repeatability analysis is necessary. Thus, the validation of each step of the methodology was performed, analyzing how variations in the images are translated to the results, and comparing them to the optometrist's measurements. Our results prove the robustness of our methodology to various conditions. Moreover, the differences in the automatic outputs are similar to the optometrist's ones

Retinal Vasculature Identification and Characterization Using OCT Imaging

The eye fundus is the part of the human body where the blood vessels can be directly observed and studied. For this reason, the analysis and diagnosis of many relevant diseases that affect the circulatory system, for example, reference, hypertension, diabetes or arteriosclerosis can be supported by the use of this source of information, analyzing their degree of severity and impact by the study of the properties of the retinal microcirculation. The development of computer aided-diagnosis tools became relevant over the recent years as they support and facilitate the work of specialists, helping to accurately identify the target structures in many processes of analysis and diagnosis. In that sense, the automatic identification of the retinal vasculature is crucial as its manual identification is an exhaustive and tedious work when it is manually performed by the experts. This chapter presents an analysis of the characteristics of the optical coherence tomography imaging and its potential for the retinal vascular identification and characterization. In that sense, we also analyze computational approaches to automatically obtain and characterize the retinal vasculature and provide an intuitive visualization that facilitates the posterior clinical analysis of relevant diseases such as hypertension or diabetes

Enhanced visualization of the retinal vasculature using depth information in OCT

This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s11517-017-1660-8[Abstract]: Retinal vessel tree extraction is a crucial step for analyzing the microcirculation, a frequently needed process in the study of relevant diseases. To date, this has normally been done by using 2D image capture paradigms, offering a restricted visualization of the real layout of the retinal vasculature. In this work, we propose a new approach that automatically segments and reconstructs the 3D retinal vessel tree by combining near-infrared reflectance retinography information with Optical Coherence Tomography (OCT) sections. Our proposal identifies the vessels, estimates their calibers, and obtains the depth at all the positions of the entire vessel tree, thereby enabling the reconstruction of the 3D layout of the complete arteriovenous tree for subsequent analysis. The method was tested using 991 OCT images combined with their corresponding near-infrared reflectance retinography. The different stages of the methodology were validated using the opinion of an expert as a reference. The tests offered accurate results, showing coherent reconstructions of the 3D vasculature that can be analyzed in the diagnosis of relevant diseases affecting the retinal microcirculation, such as hypertension or diabetes, among others.This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the PI14/02161 and the DTS15/00153 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.Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2016-04

Defining the Optimal Region of Interest for Hyperemia Grading in the Bulbar Conjunctiva

Conjunctival hyperemia or conjunctival redness is a symptom that can be associated with a broad group of ocular diseases. Its levels of severity are represented by standard photographic charts that are visually compared with the patient’s eye. This way, the hyperemia diagnosis becomes a nonrepeatable task that depends on the experience of the grader. To solve this problem, we have proposed a computer-aided methodology that comprises three main stages: the segmentation of the conjunctiva, the extraction of features in this region based on colour and the presence of blood vessels, and, finally, the transformation of these features into grading scale values by means of regression techniques. However, the conjunctival segmentation can be slightly inaccurate mainly due to illumination issues. In this work, we analyse the relevance of different features with respect to their location within the conjunctiva in order to delimit a reliable region of interest for the grading. The results show that the automatic procedure behaves like an expert using only a limited region of interest within the conjunctivaThis research has been partially supported by the Ministerio de Economía y Competitividad through the Research Contract DPI2015-69948-R. María Luisa Sánchez Brea acknowledges the support of the University of A Coruna though the Inditex-UDC Grant ProgramS

Fully automatic segmentation of the choroid in non-EDI OCT images of patients with multiple sclerosis

Emilio López Varela acknowledges its support under FPI Grant Program through PID2019-108435RB-I00 project.[Abstract]: Multiple Sclerosis (MS) is a chronic neurological disease, in which immune-mediated mechanisms lead to pathological processes of neurodegeneration. Optical coherence tomography (OCT) has recently begun to be used to diagnose and monitor patients with MS. Morphological changes in the choroid have been linked to the onset of MS, so an accurate segmentation of this layer is critical. Conventional OCT has several limitations in obtaining accurate images of the choroid, which has been improved through the use of systems such as Enhanced Depth Imaging (EDI) OCT. Unfortunately, many longitudinal studies that have collected samples over the years in the past have been performed using highly variable settings and without the use of the EDI protocol (or similar variants). For these reasons, in this work we propose a series of fully automatic approaches, based on convolutional neural networks, capable of robustly segmenting the choroid in OCT images without using the EDI protocol. To test the robustness and efficiency of our method, we performed experiments on a public dataset and a collected one. The Dice score obtained by the best proposed architecture is 89.7 for the public dataset, and 93.7 for the collected dataset.Instituto de Salud Carlos III; DTS18/00136Ministerio de Ciencia e Innovación y Universidades; RTI2018-095894-B-I00Xunta de Galicia; ED431C 2020/24Ministerio de Ciencia e Innovación; PID2019-108435RB-I00Axencia Galega de Innovación (GAIN); IN845D 2020/38Xunta de Galicia; ED431G 2019/0

State of the climate in 2018

In 2018, the dominant greenhouse gases released into Earth’s atmosphere—carbon dioxide, methane, and nitrous oxide—continued their increase. The annual global average carbon dioxide concentration at Earth’s surface was 407.4 ± 0.1 ppm, the highest in the modern instrumental record and in ice core records dating back 800 000 years. Combined, greenhouse gases and several halogenated gases contribute just over 3 W m−2 to radiative forcing and represent a nearly 43% increase since 1990. Carbon dioxide is responsible for about 65% of this radiative forcing. With a weak La Niña in early 2018 transitioning to a weak El Niño by the year’s end, the global surface (land and ocean) temperature was the fourth highest on record, with only 2015 through 2017 being warmer. Several European countries reported record high annual temperatures. There were also more high, and fewer low, temperature extremes than in nearly all of the 68-year extremes record. Madagascar recorded a record daily temperature of 40.5°C in Morondava in March, while South Korea set its record high of 41.0°C in August in Hongcheon. Nawabshah, Pakistan, recorded its highest temperature of 50.2°C, which may be a new daily world record for April. Globally, the annual lower troposphere temperature was third to seventh highest, depending on the dataset analyzed. The lower stratospheric temperature was approximately fifth lowest. The 2018 Arctic land surface temperature was 1.2°C above the 1981–2010 average, tying for third highest in the 118-year record, following 2016 and 2017. June’s Arctic snow cover extent was almost half of what it was 35 years ago. Across Greenland, however, regional summer temperatures were generally below or near average. Additionally, a satellite survey of 47 glaciers in Greenland indicated a net increase in area for the first time since records began in 1999. Increasing permafrost temperatures were reported at most observation sites in the Arctic, with the overall increase of 0.1°–0.2°C between 2017 and 2018 being comparable to the highest rate of warming ever observed in the region. On 17 March, Arctic sea ice extent marked the second smallest annual maximum in the 38-year record, larger than only 2017. The minimum extent in 2018 was reached on 19 September and again on 23 September, tying 2008 and 2010 for the sixth lowest extent on record. The 23 September date tied 1997 as the latest sea ice minimum date on record. First-year ice now dominates the ice cover, comprising 77% of the March 2018 ice pack compared to 55% during the 1980s. Because thinner, younger ice is more vulnerable to melting out in summer, this shift in sea ice age has contributed to the decreasing trend in minimum ice extent. Regionally, Bering Sea ice extent was at record lows for almost the entire 2017/18 ice season. For the Antarctic continent as a whole, 2018 was warmer than average. On the highest points of the Antarctic Plateau, the automatic weather station Relay (74°S) broke or tied six monthly temperature records throughout the year, with August breaking its record by nearly 8°C. However, cool conditions in the western Bellingshausen Sea and Amundsen Sea sector contributed to a low melt season overall for 2017/18. High SSTs contributed to low summer sea ice extent in the Ross and Weddell Seas in 2018, underpinning the second lowest Antarctic summer minimum sea ice extent on record. Despite conducive conditions for its formation, the ozone hole at its maximum extent in September was near the 2000–18 mean, likely due to an ongoing slow decline in stratospheric chlorine monoxide concentration. Across the oceans, globally averaged SST decreased slightly since the record El Niño year of 2016 but was still far above the climatological mean. On average, SST is increasing at a rate of 0.10° ± 0.01°C decade−1 since 1950. The warming appeared largest in the tropical Indian Ocean and smallest in the North Pacific. The deeper ocean continues to warm year after year. For the seventh consecutive year, global annual mean sea level became the highest in the 26-year record, rising to 81 mm above the 1993 average. As anticipated in a warming climate, the hydrological cycle over the ocean is accelerating: dry regions are becoming drier and wet regions rainier. Closer to the equator, 95 named tropical storms were observed during 2018, well above the 1981–2010 average of 82. Eleven tropical cyclones reached Saffir–Simpson scale Category 5 intensity. North Atlantic Major Hurricane Michael’s landfall intensity of 140 kt was the fourth strongest for any continental U.S. hurricane landfall in the 168-year record. Michael caused more than 30 fatalities and $25 billion (U.S. dollars) in damages. In the western North Pacific, Super Typhoon Mangkhut led to 160 fatalities and$6 billion (U.S. dollars) in damages across the Philippines, Hong Kong, Macau, mainland China, Guam, and the Northern Mariana Islands. Tropical Storm Son-Tinh was responsible for 170 fatalities in Vietnam and Laos. Nearly all the islands of Micronesia experienced at least moderate impacts from various tropical cyclones. Across land, many areas around the globe received copious precipitation, notable at different time scales. Rodrigues and Réunion Island near southern Africa each reported their third wettest year on record. In Hawaii, 1262 mm precipitation at Waipā Gardens (Kauai) on 14–15 April set a new U.S. record for 24-h precipitation. In Brazil, the city of Belo Horizonte received nearly 75 mm of rain in just 20 minutes, nearly half its monthly average. Globally, fire activity during 2018 was the lowest since the start of the record in 1997, with a combined burned area of about 500 million hectares. This reinforced the long-term downward trend in fire emissions driven by changes in land use in frequently burning savannas. However, wildfires burned 3.5 million hectares across the United States, well above the 2000–10 average of 2.7 million hectares. Combined, U.S. wildfire damages for the 2017 and 2018 wildfire seasons exceeded $40 billion (U.S. dollars)

Plan de comunicación de la empresa Cíclika

El presente Trabajo Fin de Máster está enfocado hacia la formulación de la estrategia comunicativa materializada en un plan de comunicación, el primero y único diseñado para la empresa Cíclika, el sueño de dos ingenieros apasionados por la tecnología, la innovación y el espíritu emprendedor convertido en una empresa tecnológica que se encuentra en pleno desarrollo.El present Treballe Fi de Màster està enfocat cap a la formulació de l'estratègia comunicativa materialitzada en un pla de comunicació, el primer i únic dissenyat per a l'empresa Cíclika, el somni de dos enginyers apassionats per la tecnologia, la innovació i l'esperit emprenedor convertit en una empresa tecnològica que es troba en ple desenvolupament.The present Master's End Project is focused on the formulation of the communicative strategy materialized in a communication plan, the first and only designed for the Cyclic company, the dream of two engineers passionate about technology, innovation and the spirit started to become A technological company that is in full development

Automatic Characterization of Epiretinal Membrane in OCT Images with Supervised Training

This work presents an automatic method to characterize the presence or absence of the epiretinal membrane (ERM) in Optical Coherence Tomography (OCT) images. To this end, a predefined set of classifiers is used on multiple local-based feature vectors which represent the inner limiting membrane (ILM), the layer of the retina where the ERM can be present

Automatic System for the Identification and Visualization of the Retinal Vessel Tree Using OCT Imaging

This paper proposes a system for the three-dimensional identification and visualization of the retinal vasculature using Optical Coherence Tomography (OCT) scans. This fully automatic tool provides useful biomarkers to the medical specialists that facilitate the prevention, diagnosis and treatment of various retinal and systemic pathologies