Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis

[Abstract] Background and objectives The analysis of the interference patterns on the tear film lipid layer is a useful clinical test to diagnose dry eye syndrome. This task can be automated with a high degree of accuracy by means of the use of tear film maps. However, the time required by the existing applications to generate them prevents a wider acceptance of this method by medical experts. Multithreading has been previously successfully employed by the authors to accelerate the tear film map definition on multicore single-node machines. In this work, we propose a hybrid message-passing and multithreading parallel approach that further accelerates the generation of tear film maps by exploiting the computational capabilities of distributed-memory systems such as multicore clusters and supercomputers. Methods The algorithm for drawing tear film maps is parallelized using Message Passing Interface (MPI) for inter-node communications and the multithreading support available in the C++11 standard for intra-node parallelization. The original algorithm is modified to reduce the communications and increase the scalability. Results The hybrid method has been tested on 32 nodes of an Intel cluster (with two 12-core Haswell 2680v3 processors per node) using 50 representative images. Results show that maximum runtime is reduced from almost two minutes using the previous only-multithreaded approach to less than ten seconds using the hybrid method. Conclusions The hybrid MPI/multithreaded implementation can be used by medical experts to obtain tear film maps in only a few seconds, which will significantly accelerate and facilitate the diagnosis of the dry eye syndrome.Ministerio de Economía y Competitividad; TIN2013-42148-PPortugal. Fundação para a Ciência e a Tecnologia; POCI-01-0145-FEDER-006961Portugal. Fundação para a Ciência e a Tecnologia; UID/EEA/50014/2013Portugal. Fundação para a Ciência e a Tecnologia; SFRH/BPD/111177/2015

Advancing the diagnosis of dry eye syndrome : development of automated assessments of tear film lipid layer patterns

[Resumen] El síndrome de ojo seco es una enfermedad sintomática que afecta a un amplio rango de la población, y tiene un impacto negativo en sus actividades diarias. Su diagnóstico es una tarea difícil debido a su etiología multifactorial, y por eso existen varias pruebas clínicas. Una de esas pruebas es la evaluación de los patrones interferenciales de la capa lipídica de la película lagrimal. Guillon dise˜nó un instrumento denominado Tearscope Plus para evaluar el grosor de la película lagrimal de forma rápida, y también definió una escala de clasificación compuesta de cinco categorías. La clasificación en uno de esos cinco patrones es una tarea clínica dificil, especialmente con las capas lipídicas más finas que carecen de características de color y/o morfológicas. Además, la interpretación subjetiva de los expertos mediante una revisión visual puede afectar a la clasificación, pudiendo producirse un alto grado de inter- e intra- variabilidad entre observadores. El desarrollo de un método sistemático y objetivo para análisis y clasificación es altamente deseable, permitiendo un diagnóstico homogéneo y liberando a los expertos de esta tediosa tarea. La propuesta de esta investigación es el diseño de un sistema automático para evaluar los patrones de la capa lipídica de la película lagrimal mediante la interpretación de las imágenes obtenidas con el Tearscope Plus. Por una parte, se presenta una metodología global para evaluar la capa lipídica de la película lagrimal mediante la clasificación automática de estas imágenes en una de las categorías de Guillon. El proceso se lleva a cabo mediante el uso de modelos de textura y color, y algoritmos de aprendizaje máquina. A continuación, esta metodología global se optimiza mediante la reducción de su complejidad computacional. Se utilizan técnicas de reducción de la dimensión para disminuir los requisitos de memoria/tiempo sin una degradación en su rendimiento. Por otra parte, se presenta una metodología local para crear mapas de la película lagrimal, que representan la distribución local de los patrones de la capa lipídica sobre la película lagrimal. Las diferentes evaluaciones automáticas que se proponen ahorran tiempo a los expertos, y proporcionan resultados imparciales que no están afectados por factores subjetivos.[Resumo] O síndrome de ollo seco é unha enfermidade sintomática que afecta a un amplo rango da poboación, e ten un impacto negativo nas súas actividades diarias. O seu diagnóstico é unha tarefa difícil debido á súa etioloxía multifactorial, e por iso existen varias probas clínicas. Unha desas probas é a avaliación dos patróns interferenciais da capa lipídica da película lagrimal. Guillon dese˜nou un instrumento denominado Tearscope Plus para avaliar o grosor da película lagrimal de forma rápida, e tamén definiu unha escala de clasificación composta de cinco categorías. A clasificación nun deses cinco patróns é unha tarefa clínica difícil, especialmente coas capas lipídicas máis finas que carecen de características de cor e/ou morfolóxicas. Ademais, a interpretación subxectiva dos expertos mediante una revisión visual pode afectar á clasificación, podendo producirse un alto grao de inter- e intra- variabilidade entre observadores. O desenvolvemento dun método sistemático e obxectivo para análise e clasificación é altamente desexable, permitindo un diagnóstico homoxéneo e liberando aos expertos desta tediosa tarefa. A proposta desta investigación é o deseño dun sistema automático para avaliar os patróns da capa lipídica da película lagrimal mediante a interpretación das imaxes obtidas co Tearscope Plus. Por unha parte, preséntase unha metodoloxía global para avaliar a capa lipídica da película lagrimal mediante a clasificación automática destas imaxes nunha das categorías de Guillon. O proceso é levado a cabo mediante o uso de modelos de textura e cor, e algoritmos de aprendizaxe máquina. A continuación, esta metodoloxía global é optimizada mediante a redución da súa complexidade computacional. Utilízanse técnicas de redución da dimensión para diminuír os requisitos de memoria/tempo sen unha degradación no seu rendemento. Por outra parte, preséntase unha metodoloxía local para crear mapas da película lagrimal, que representan a distribución local dos patróns da capa lipídica sobre a película lagrimal. As diferentes avaliacións automáticas que se propoñen aforran tempo aos expertos, e proporcionan resultados imparciais que non están afectados por factores subxectivos.[Abstract] Dry eye syndrome is a symptomatic disease which affects a wide range of population, and has a negative impact on their daily activities. Its diagnosis is a difficult task due to its multifactorial etiology, and so there exist several clinical tests. One of these tests is the evaluation of the interference patterns of the tear film lipid layer. Guillon designed an instrument known as Tearscope Plus which allows clinicians to rapidly assess the lipid layer thickness, and also defined a grading scale composed of five categories. The classification into these five patterns is a difficult clinical task, especially with thinner lipid layers which lack color and/or morphological features. Furthermore, the subjective interpretation of the experts via visual inspection may affect the classification, and so a high degree of inter- and also intra- observer variability can be produced. The development of a systematic, objective computerized method for analysis and classification is thus highly desirable, allowing for homogeneous diagnosis and relieving the experts from this tedious task. The proposal of this research is the design of an automatic system to assess the tear film lipid layer patterns through the interpretation of the images acquired with the Tearscope Plus. On the one hand, a global methodology is presented to assess the tear film lipid layer by automatically classifying these images into the Guillon categories. The process is carried out using texture and color models, and machine learning algorithms. Then, this global methodology is optimized through the reduction of its computational complexity. Dimensionality reduction techniques are used in order to diminish the memory/time requirements with no degradation in performance. On the other hand, a local methodology is also presented to create tear film maps, which represent the local distribution of the lipid layer patterns over the tear film. The different automated assessments proposed save time for experts, and provide unbiased results which are not affected by subjective factors

A review of artificial intelligence applications in anterior segment ocular diseases

Background: Artificial intelligence (AI) has great potential for interpreting and analyzing images and processing large amounts of data. There is a growing interest in investigating the applications of AI in anterior segment ocular diseases. This narrative review aims to assess the use of different AI-based algorithms for diagnosing and managing anterior segment entities. Methods: We reviewed the applications of different AI-based algorithms in the diagnosis and management of anterior segment entities, including keratoconus, corneal dystrophy, corneal grafts, corneal transplantation, refractive surgery, pterygium, infectious keratitis, cataracts, and disorders of the corneal nerves, conjunctiva, tear film, anterior chamber angle, and iris. The English-language databases PubMed/MEDLINE, Scopus, and Google Scholar were searched using the following keywords: artificial intelligence, deep learning, machine learning, neural network, anterior eye segment diseases, corneal disease, keratoconus, dry eye, refractive surgery, pterygium, infectious keratitis, anterior chamber, and cataract. Relevant articles were compared based on the use of AI models in the diagnosis and treatment of anterior segment diseases. Furthermore, we prepared a summary of the diagnostic performance of the AI-based methods for anterior segment ocular entities. Results: Various AI methods based on deep and machine learning can analyze data obtained from corneal imaging modalities with acceptable diagnostic performance. Currently, complicated and time-consuming manual methods are available for diagnosing and treating eye diseases. However, AI methods could save time and prevent vision impairment in eyes with anterior segment diseases. Because many anterior segment diseases can cause irreversible complications and even vision loss, sufficient confidence in the results obtained from the designed model is crucial for decision-making by experts. Conclusions: AI-based models could be used as surrogates for analyzing manual data with improveddiagnostic performance. These methods could be reliable tools for diagnosing and managing anterior segmentocular diseases in the near future in remote areas. It is expected that future studies can design algorithms thatuse less data in a multitasking manner for the detection and management of anterior segment diseases

Detection of dirt impairments from archived film sequences : survey and evaluations

Film dirt is the most commonly encountered artifact in archive restoration applications. Since dirt usually appears as a temporally impulsive event, motion-compensated interframe processing is widely applied for its detection. However, motion-compensated prediction requires a high degree of complexity and can be unreliable when motion estimation fails. Consequently, many techniques using spatial or spatiotemporal filtering without motion were also been proposed as alternatives. A comprehensive survey and evaluation of existing methods is presented, in which both qualitative and quantitative performances are compared in terms of accuracy, robustness, and complexity. After analyzing these algorithms and identifying their limitations, we conclude with guidance in choosing from these algorithms and promising directions for future research

Currency security and forensics: a survey

By its definition, the word currency refers to an agreed medium for exchange, a nation’s currency is the formal medium enforced by the elected governing entity. Throughout history, issuers have faced one common threat: counterfeiting. Despite technological advancements, overcoming counterfeit production remains a distant future. Scientific determination of authenticity requires a deep understanding of the raw materials and manufacturing processes involved. This survey serves as a synthesis of the current literature to understand the technology and the mechanics involved in currency manufacture and security, whilst identifying gaps in the current literature. Ultimately, a robust currency is desire

Advancing the diagnosis of Dry Eye Syndrome : development of dynamic, automated tear film Break-Up assessment

[Resumen] El síndrome de ojo seco es un trastorno común de la película lagrimal que afecta a un sector significativo de la población, impactando en la calidad de vida. El diagnóstico de esta enfermedad es difícil debido a su etiología multifactorial, por lo que hay varias pruebas clínicas para evaluar diferentes aspectos de la película lagrimal. Una de las pruebas empleadas habitualmente es el test de BUT, que consiste en medir el tiempo transcurrido desde el último parpadeo hasta la ruptura de la película lagrimal, representada por la aparición de áreas oscuras que corresponden al adelgazamiento de la película lagrimal en la superficie ocular. Además del tiempo, hay varias características de la ruptura como la zona, la forma, el tamaño y la evolución, que podrían afectar a la severidad del síndrome de ojo seco. Sin embargo, el test de BUT presenta una baja repetibilidad debido principalmente a la apreciación subjetiva de los puntos oscuros, las diferencias entre expertos y la variabilidad de la película lagrimal. Además, la caracterización a mano de las zonas de ruptura es una tarea tediosa que consume mucho tiempo. La automatización del análisis de la ruptura reduciría su carácter subjetivo, permitiendo una evaluación más precisa de la película lagrimal. Este trabajo presenta una metodología novel para una evaluación de la ruptura de la película lagrimal totalmente automática. Este estudio permite un análisis cuantitativo y cualitativo de la inestabilidad de la película lagrimal como una extensi´on de la medida de BUT, que se centra solo en el tiempo. Esta metodolog´ıa proporciona resultados de precisión en los mismos rangos que entre los propios expertos. Así, la evaluación automática de la ruptura ahorra tiempo a los expertos proporcionando resultados imparciales que no están afectados por factores subjetivos.Resumo O síndrome de ollo seco é un trastorno común da película lacrimal que afecta a un sector significativo da poboación, impactando na calidade de vida. A diagnose desta enfermidade é difícil debido a súa etioloxía multifactorial, polo que hai varias probas clínicas para avaliar diferentes aspectos da película lacrimal. Unha das probas empregadas habitualmente é o test de BUT (Break-Up Time), que consiste en medir o tempo transcorrido dende o último pestanexo ata a ruptura da película lacrimal, representada pola aparición de áreas escuras que corresponden ó adelgazamento da película lacrimal na superficie ocular. Ademais do tempo, hai varias características da ruptura como a zona, forma, tamaño e evolución, que poderían afectar á severidade do síndrome de ollo seco. Sen embargo, o test de BUT presenta unha baixa repetibilidade debido principalmente á apreciación subxectiva dos puntos escuros, ás diferencias entre expertos e á variabilidade da película lacrimal. Ademais, a caracterización á man das zonas de ruptura é unha tarefa tediosa que consume moito tempo. A automatización da análise da ruptura reduciría o seu carácter subxectivo, permitindo unha avaliación máis precisa da película lacrimal. Este traballo presenta unha metodoloxía novel para unha avaliación da ruptura da película lacrimal totalmente automática. Este estudo permite unha análise cualitativa e cuantitativa da inestabilidade da película lacrimal como unha extensión da medida de BUT, que se centra só no tempo. Esta metodoloxía proporciona resultados de precisión nos mesmos rangos que entre os propios expertos. Deste xeito, a avaliación automática da ruptura aforra tempo ós expertos proporcionando resultados imparciais que non están afectados por factores subxectivos.[Abstract] Dry Eye Syndrome (DES) is a common disorder of the tear film which affects a significant sector of the population, impacting on quality of life. The diagnosis of this condition is difficult due to its multifactorial etiology, so there are a wide number of tests to evaluate different aspects of the tear film. Among the different tests available, the Break-up Time test (BUT) is a widely used measure to evaluate the quality and stability of the tear film on the ocular surface. It consists in measuring the time elapsed since the last blink until the tear film break-up, that is, the appearance of dark areas related to a thinning of the tear film on the surface of the eye. Besides the time, there are several break-up features such as the location, shape, size and dynamics of the breakup areas, which could affect to dry eye severity. However, the BUT test is affected by low repeatability mainly due to a subjective appreciation of the dark spots, the differences among the experts, and the variability of the tear film. Furthermore, the characterization by hand of break-up areas is a tedious and time consuming task. The automation of the break-up assessment would reduce its subjective character, allowing a more accurate evaluation of tear film stability. This work presents a novel methodology for a fully automatic assessment of the tear film break-up. The proposed methodology allows a quantitative, qualitative analysis of tear film instability, as an extension of BUT measurement, which is focused only on time. It provides accuracy results that are in the same ranges as the experts themselves. Therefore, the automated breakup assessment saves time for experts providing unbiased results which are not affected by subjective factors

Application of infrared thermography in computer aided diagnosis

The invention of thermography, in the 1950s, posed a formidable problem to the research community: What is the relationship between disease and heat radiation captured with Infrared (IR) cameras? The research community responded with a continuous effort to find this crucial relationship. This effort was aided by advances in processing techniques, improved sensitivity and spatial resolution of thermal sensors. However, despite this progress fundamental issues with this imaging modality still remain. The main problem is that the link between disease and heat radiation is complex and in many cases even non-linear. Furthermore, the change in heat radiation as well as the change in radiation pattern, which indicate disease, is minute. On a technical level, this poses high requirements on image capturing and processing. On a more abstract level, these problems lead to inter-observer variability and on an even more abstract level they lead to a lack of trust in this imaging modality. In this review, we adopt the position that these problems can only be solved through a strict application of scientific principles and objective performance assessment. Computing machinery is inherently objective; this helps us to apply scientific principles in a transparent way and to assess the performance results. As a consequence, we aim to promote thermography based Computer-Aided Diagnosis (CAD) systems. Another benefit of CAD systems comes from the fact that the diagnostic accuracy is linked to the capability of the computing machinery and, in general, computers become ever more potent. We predict that a pervasive application of computers and networking technology in medicine will help us to overcome the shortcomings of any single imaging modality and this will pave the way for integrated health care systems which maximize the quality of patient care

The comparative evaluation of ERTS-1 imagery for resource inventory in land use planning

The author has identified the following significant results. Multidiscipline team interpretation and mapping of resources for Crook County is complete on 1:250,000 scale enlargements of ERTS imagery and 1:120,000 hi-flight photography. Maps of geology, soils, vegetation-land use and land resources units were interpreted to show limitations, suitabilities, and geologic hazards for land use planning. Mapping of lineaments and structures from ERTS imagery has shown a number of features not previously mapped in Oregon. A multistage timber inventory of Ochoco National Forest was made, using ERTS images as the first stage. Inventory of forest clear-cutting practices was successfully demonstrated with color composites. Soil tonal differences in fallow fields correspond with major soil boundaries in loess-mantled terrain. A digital classification system used for discriminating natural vegetation and geologic material classes was successful in separating most major classes around Newberry Caldera, Mt. Washington, and Big Summit Prairie