Automated Identification of Diabetic Retinopathy: A Survey

Diabetes strikes when the pancreas stops to produce sufficient insulin, gradually disturbing the retina of the human eye, leading to diabetic retinopathy. The blood vessels in the retina become changed and have abnormality. Exudates are concealed, micro-aneurysms and haemorrhages occur in the retina of eye, which intern leads to blindness. The presence of these structures signifies the harshness of the disease. A systematized Diabetic Retinopathy screening system will enable the detection of lesions accurately, consequently facilitating the ophthalmologists. Micro-aneurysms are the initial clinical signs of diabetic retinopathy. Timely identification of diabetic retinopathy plays a major role in the success of managing the disease. The main task is to extract exudates, which are similar in color property and size of the optic disk; afterwards micro-aneurysms are alike in color and closeness with blood vessels. The primary objective of this review is to survey the methods, techniques potential benefits and limitations of automated detection of micro-aneurysm in order to better manage translation into clinical practice, based on extensive experience with systems used by opthalmologists treating diabetic retinopathy

Psychiatric Case Record

Bipolar Disorder-Mania: Patient was apparently normal one-month back, Then all of a sudden he developed sleep disturbances –mainly difficult in initiation of sleep. He also started abusing his family members for unwanted things. Subsequently, he started talking excessively and irritable. Sometimes he sings film songs and dances. He used to say that God Supreme exists in himself and so he has all the powers of Almighty. With that superior power he says that he can solve all the problems in this world. He also says that he has invented herbs to keep people young. For the past one week, he talks excessively without having an hour of sleep & wanders here and there & found excessively smoking. He becomes excessively spiritual and goes to near by villages for offering prayers to God. He takes only a little food everyday and he is very much keen in personal cleanliness. Paranoid Schizophrenia: She was apparently normal 8 months back, then she developed sleep disturbances in the form of difficult in falling asleep. She was found talking & smiling to herself at night & day with mirror gazing. She started saying that her neighbour & relatives are planning to kill herself by poisoning. In this context she had frequent quarrels with them and she refused to take food prepared by her mother in law. She left the home at night without informing any one and started wandering in the road side near her home. She was complaining that she hears voices as if her neighbour & relatives were talking about her among themselves She was not doing house hold activities for past 6 months and she was not taking care of her child. Her personal hygiene was very much deteriorated slowly as she used to take bath & brush, only if she was asked to do so. She started abusing & assaulting the strangers and family members. Generalised Anxiety Disorder: Six months back he was apparently normal. He is working as a system analyst in a private bank . He had once, made a mistake in his bank work for which he was given charges by his employer, followed this event he becomes very tense and afraid whenever his boss called him. He is very cautious that he should not commit any mistakes. Even though he is not doing so, he fears that he may commit some mistake in his work. At that moment he develops palpitation, giddiness, breathlessness, excessive sweating over palms and soles. Slowly these symptoms present through out the day even when he was not in his office, and he could not control his fearfulness. For the past 6 months he didn’t sleep well. His sleep is disturbed by bad dreams. Recurrent Depressive Disorder: Patient was apparently alright 2 months back. Then she developed sleep disturbances particularly early morning awakening, she use to wake up by 3.00 am and use to brood about herself and started crying. She was not doing her domestic work as before, as she felt excess tiredness and use to take frequent rests. She developed poor communication. She had lost her interest in pleasurable activities and was not interested in watching TV, and attending family gatherings. She stayed aloof most of the time & calm, quiet and withdrawn. She was expressing her helplessness and hopelessness about the future. She started to have decline in maintaining self care. 15 days back, she frequently expressed suicidal ideas and she had attempted suicide by hanging herself and was rescued by neighbours. 5 days back, she started talking in an irrelevant manner. She was smiling to self. She was assaulting her family members. She was suspicious that her neighbour had done black magic on her and also saying that people are talking about her. She reported hearing the voice of her neighbour scolding and threatening her. Organic Brain Syndrome – Dementia: Ten months back he was apparently alright. Then his relatives noticed himself frequently misplaces things inside his home. Then he started behaving aggressively. He was beating his wife without reason. He was roaming here and there, running out of home and wandering aimlessly. He was not able to come back home when he goes out. He was brought back to home by his relatives. Slowly he developed fearfulness and tremulousness while he was staying alone. He also started saying that his family members & neighbours were talking about himself, in this context he would make frequent quarrels with them. He also started hearing voices of known male voices abusing himself in third person. He sleeps for few hour only. He is passing urine and motion inside the house. He is asking about his brother and mother-in-law who were expired long back. He behaves abnormally such as pouring water in the plate while eating. And his relatives found the symptoms were worsened by evening. All these symptoms started insidiously, increased in severity through time and attained the present state. No history of loss of appetite / crying spells / suicidal tendencies / convulsions / fever / head injury

A Decision Support Framework for Automated Screening of Diabetic Retinopathy

The early signs of diabetic retinopathy (DR) are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS) for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity

Handheld image acquisition with real-time vision for human-computer interaction on mobile applications

Tese de mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica), Universidade de Lisboa, Faculdade de Ciências, 2019Várias patologias importantes manifestam-se na retina, sendo que estas podem ter origem na própria retina ou então provirem de doenças sistémicas. A retinopatia diabética, o glaucoma e a degeneração macular relacionada com a idade são algumas dessas patologias oculares, e também as maiores causas de cegueira nos países desenvolvidos. Graças à maior prevalência que se tem verificado, tem havido uma aposta cada vez maior na massificação do rastreio destas doenças, principalmente na população mais suscetível de as contrair. Visto que a retina é responsável pela formação de imagens, ou seja, pelo sentido da visão, os componentes oculares que estão localizados anteriormente têm de ser transparentes, permitindo assim a passagem da luz. Isto faz com que a retina e, por sua vez, o tecido cerebral, possam ser examinados de forma não-invasiva. Existem várias técnicas de imagiologia da retina, incluindo a angiografia fluoresceínica, a tomografia de coerência ótica e a retinografia. O protótipo EyeFundusScope (EFS) da Fraunhofer é um retinógrafo portátil, acoplado a um smartphone, que permite a obtenção de imagens do fundo do olho, sem que seja necessária a dilatação da pupila. Utiliza um algoritmo de aprendizagem automática para detetar lesões existentes na retina, que estão normalmente associadas a um quadro de retinopatia diabética. Para além disso, utiliza um sistema de suporte à decisão, que indica a ausência ou presença da referida retinopatia. A fiabilidade deste tipo de algoritmos e o correto diagnóstico por parte de oftalmologistas e neurologistas estão extremamente dependentes da qualidade das imagens adquiridas. A consistência da captura portátil, com este tipo de retinógrafos, está intimamente relacionada com uma interação apropriada com o utilizador. De forma a melhorar o contributo prestado pelo utilizador, durante o procedimento habitual da retinografia, foi desenvolvida uma nova interface gráfica de utilizador, na aplicação Android do EFS. A abordagem pretendida consiste em tornar o uso do EFS mais acessível, e encorajar técnicos não especializados a utilizarem esta técnica de imagem médica, tanto em ambiente clínico como fora deste. Composto por vários elementos de interação, que foram criados para atender às necessidades do protocolo de aquisição de imagem, a interface gráfica de utilizador deverá auxiliar todos os utilizadores no posicionamento e alinhamento do EFS com a pupila do doente. Para além disto, poderá existir um controlo personalizado do tempo despendido em aquisições do mesmo olho. Inicialmente, foram desenhadas várias versões dos elementos de interação rotacionais, sendo posteriormente as mesmas implementadas na aplicação Android. Estes elementos de interação utilizam os dados recolhidos dos sensores inerciais, já existentes no smartphone, para transmitir uma resposta em tempo real ao utilizador enquanto este move o EFS. Além dos elementos de interação rotacionais, também foram implementados um temporizador e um indicador do olho que está a ser examinado. Após a implementação de três configurações com as várias versões dos elementos de interação, procedeu-se à realização dos testes de usabilidade. No entanto, antes desta etapa se poder concretizar, foram realizados vários acertos e correções com a ajuda de um olho fantoma. Durante o planeamento dos testes de usabilidade foi estabelecido um protocolo para os diferentes cenários de uso e foi criado um tutorial com as principais cautelas que os utilizadores deveriam ter aquando das aquisições. Os resultados dos testes de usabilidade mostram que a nova interface gráfica teve um efeito bastante positivo na experiência dos utilizadores. A maioria adaptou-se rapidamente à nova interface, sendo que para muitos contribuiu para o sucesso da tarefa de aquisição de imagem. No futuro, espera-se que a combinação dos dados fornecidos pelos sensores inerciais, juntamente com a implementação de novos algoritmos de reconhecimento de imagem, sejam a base de uma nova e mais eficaz técnica de interação em prática clínica. Além disso, a nova interface gráfica poderá proporcionar ao EFS uma aplicação que sirva exclusivamente para efeitos de formação profissional.Many important diseases manifest themselves in the retina, both primary retinal conditions and systemic disorders. Diabetic retinopathy, glaucoma and age-related macular degeneration are some of the most frequent ocular disorders and the leading causes of blindness in developed countries. Since these disorders are becoming increasingly prevalent, there has been the need to encourage high coverage screening among the most susceptible population. As its function requires the retina to see the outside world, the involved optical components must be transparent for image formation. This makes the retinal tissue, and thereby brain tissue, accessible for imaging in a non-invasive manner. There are several approaches to visualize the retina including fluorescein angiography, optical coherence tomography and fundus photography. The Fraunhofer’s EyeFundusScope (EFS) prototype is a handheld smartphone-based fundus camera, that doesn’t require pupil dilation. It employs advanced machine learning algorithms to process the image in search of lesions that are often associated with diabetic retinopathy, making it a pre-diagnostic tool. The robustness of this computer vision algorithm, as well as the diagnose performance of ophthalmologists and neurologists, is strongly related with the quality of the images acquired. The consistency of handheld capture deeply depends on proper human interaction. In order to improve the user’s contribution to the retinal acquisition procedure, a new graphical user interface was designed and implemented in the EFS Acquisition App. The intended approach is to make the EFS easier to use by non-ophthalmic trained personnel, either in a non-clinical or in a clinical environment. Comprised of several interaction elements that were created to suit the needs of the acquisition procedure, the graphical user interface should help the user to position and align the EFS illumination beam with the patient’s pupil as well as keeping track of the time between acquisitions on the same eye. Initially, several versions of rotational interaction elements were designed and later implemented on the EFS Acquisition App. These used data from the smartphone’s inertial sensors to give real-time feedback to the user while moving the EFS. Besides the rotational interactional elements, a time-lapse and an eye indicator were also designed and implemented in the EFS. Usability tests took place, after three assemblies being successfully implemented and corrected with the help of a model eye ophthalmoscope trainer. Also, a protocol for the different use-case scenarios was elaborated, and a tutorial was created. Results from the usability tests, show that the new graphical user interface had a very positive outcome. The majority of users adapted very quickly to the new interface, and for many it contributed for a successful acquisition task. In the future, the grouping of inertial sensors data and image recognition may prove to be the foundations for a more efficient interaction technique performed in clinical practices. Furthermore, the new graphical user interface could provide the EFS with an application for educational purposes

Retinal vessel segmentation using textons

Segmenting vessels from retinal images, like segmentation in many other medical image domains, is a challenging task, as there is no unified way that can be adopted to extract the vessels accurately. However, it is the most critical stage in automatic assessment of various forms of diseases (e.g. Glaucoma, Age-related macular degeneration, diabetic retinopathy and cardiovascular diseases etc.). Our research aims to investigate retinal image segmentation approaches based on textons as they provide a compact description of texture that can be learnt from a training set. This thesis presents a brief review of those diseases and also includes their current situations, future trends and techniques used for their automatic diagnosis in routine clinical applications. The importance of retinal vessel segmentation is particularly emphasized in such applications. An extensive review of previous work on retinal vessel segmentation and salient texture analysis methods is presented. Five automatic retinal vessel segmentation methods are proposed in this thesis. The first method focuses on addressing the problem of removing pathological anomalies (Drusen, exudates) for retinal vessel segmentation, which have been identified by other researchers as a problem and a common source of error. The results show that the modified method shows some improvement compared to a previously published method. The second novel supervised segmentation method employs textons. We propose a new filter bank (MR11) that includes bar detectors for vascular feature extraction and other kernels to detect edges and photometric variations in the image. The k-means clustering algorithm is adopted for texton generation based on the vessel and non-vessel elements which are identified by ground truth. The third improved supervised method is developed based on the second one, in which textons are generated by k-means clustering and texton maps representing vessels are derived by back projecting pixel clusters onto hand labelled ground truth. A further step is implemented to ensure that the best combinations of textons are represented in the map and subsequently used to identify vessels in the test set. The experimental results on two benchmark datasets show that our proposed method performs well compared to other published work and the results of human experts. A further test of our system on an independent set of optical fundus images verified its consistent performance. The statistical analysis on experimental results also reveals that it is possible to train unified textons for retinal vessel segmentation. In the fourth method a novel scheme using Gabor filter bank for vessel feature extraction is proposed. The ii method is inspired by the human visual system. Machine learning is used to optimize the Gabor filter parameters. The experimental results demonstrate that our method significantly enhances the true positive rate while maintaining a level of specificity that is comparable with other approaches. Finally, we proposed a new unsupervised texton based retinal vessel segmentation method using derivative of SIFT and multi-scale Gabor filers. The lack of sufficient quantities of hand labelled ground truth and the high level of variability in ground truth labels amongst experts provides the motivation for this approach. The evaluation results reveal that our unsupervised segmentation method is comparable with the best other supervised methods and other best state of the art methods

Vessel identification in diabetic retinopathy

Diabetic retinopathy is the single largest cause of sight loss and blindness in 18 to 65 year olds. Screening programs for the estimated one to six per- cent of the diabetic population have been demonstrated to be cost and sight saving, howeverthere are insufficient screening resources. Automatic screen-ing systems may help solve this resource short fall. This thesis reports on research into an aspect of automatic grading of diabetic retinopathy; namely the identification of the retinal blood vessels in fundus photographs. It de-velops two vessels segmentation strategies and assess their accuracies. A literature review of retinal vascular segmentation found few results, and indicated a need for further development. The two methods for vessel segmentation were investigated in this thesis are based on mathematical morphology and neural networks. Both methodologies are verified on independently labeled data from two institutions and results are presented that characterisethe trade off betweenthe ability to identify vesseland non-vessels data. These results are based on thirty five images with their retinal vessels labeled. Of these images over half had significant pathology and or image acquisition artifacts. The morphological segmentation used ten images from one dataset for development. The remaining images of this dataset and the entire set of 20 images from the seconddataset were then used to prospectively verify generaliastion. For the neural approach, the imageswere pooled and 26 randomly chosenimageswere usedin training whilst 9 were reserved for prospective validation. Assuming equal importance, or cost, for vessel and non-vessel classifications, the following results were obtained; using mathematical morphology 84% correct classification of vascular and non-vascular pixels was obtained in the first dataset. This increased to 89% correct for the second dataset. Using the pooled data the neural approach achieved 88% correct identification accuracy. The spread of accuracies observed varied. It was highest in the small initial dataset with 16 and 10 percent standard deviation in vascular and non-vascular cases respectively. The lowest variability was observed in the neural classification, with a standard deviation of 5% for both accuracies. The less tangible outcomes of the research raises the issueof the selection and subsequent distribution of the patterns for neural network training. Unfortunately this indication would require further labeling of precisely those cases that were felt to be the most difficult. I.e. the small vessels and border conditions between pathology and the retina. The more concrete, evidence based conclusions,characterise both the neural and the morphological methods over a range of operating points. Many of these operating points are comparable to the few results presented in the literature. The advantage of the author's approach lies in the neural method's consistent as well as accurate vascular classification