A new method of correcting uneven illumination problem in fundus images

Recent advancements in signal and image processing have reduced the time of diagnoses, effort and pressure on the screeners by providing auto diagnostic tools for different diseases. The success rate of these tools greatly depend on the quality of acquired images. Bad image quality can significantly reduce the specificity and the sensitivity which in turn forces screeners back to their tedious job of manual diagnoses. In acquired fundus images, some areas appear to be brighter than the other, that is areas close to the center of the image are always well illuminated, hence appear very bright while areas far from the center are poorly illuminated hence appears to be very dark. Several techniques including the simple thresholding, Naka Rushton (NR) filtering technique and histogram equalization (HE) method have been suggested by various researchers to overcome this problem. However, each of these methods has limitations at their own and hence the need to develop a more robust technique that will provide better performance with greater flexibility. A new method of compensating uneven (irregular) illumination in fundus images termed global-local adaptive histogram equalization using partially-overlapped windows (GLAPOW) is proposed in this paper. The developed algorithm has been tested and the results obtained show superior performance when compared to other known techniques for uneven illumination correction

A new method of correcting uneven illumination problem in fundus image

Recent advancements in signal and image processing have reduced the time of diagnoses, effort and pressure on the screeners by providing auto diagnostic tools for different diseases. The success rate of these tools greatly depend on the quality of acquired images. Bad image quality can significantly reduce the specificity and the sensitivity which in turn forces screeners back to their tedious job of manual diagnoses. In acquired fundus images, some areas appear to be brighter than the other, that is areas close to the center of the image are always well illuminated, hence appear very bright while areas far from the center are poorly illuminated hence appears to be very dark. Several techniques including the simple thresholding, Naka Rushton (NR) filtering technique and histogram equalization (HE) method have been suggested by various researchers to overcome this problem. However, each of these methods has limitations at their own and hence the need to develop a more robust technique that will provide better performance with greater flexibility. A new method of compensating uneven (irregular) illumination in fundus images termed global-local adaptive histogram equalization using partially-overlapped windows (GLAPOW) is proposed in this paper. The developed algorithm has been tested and the results obtained show superior performance when compared to other known techniques for uneven illumination correction

Identificação de estruturas retinianas para a deteção de retinopatia diabética

A Diabetes Mellitus constitui um grave problema mundial que está a crescer exponencialmente com o passar dos anos em todo o mundo, tanto nos países desenvolvidos como nos países em desenvolvimento. Esta patologia tem repercussões por todo o organismo sendo que a nível ocular a patologia mais preocupante é a Retinopatia Diabética, uma vez que pode levar à cegueira. Esta patologia só é detetada a partir de certos exames médicos e não apresenta sintomas até um que a doença esteja num estado muito avançado. A Retinopatia Diabética cursa entre vários estágios clínicos, que são definidos pelas diferentes características oftalmológicas encontradas. Os microaneurismas são as primeiras características a aparecer, seguidas de hemorragias e exsudatos. A progressão da doença leva a um estágio mais avançado no qual surge inícios de isquémia que culmina com o crescimento de novos vasos sanguíneos. O tratamento passa primariamente pela prevenção através de uma monitorização cuidadosa em pacientes com Diabetes, que devem fazer exames oftalmológicos pelo menos uma vez por ano. Em estados mais avançados tem que se recorrer a tratamentos por laser. Como estas técnicas não recuperam totalmente a visão a prevenção é muito importante e a automatização de processos de rastreio são um tema em crescimento e de importância elevada para a sociedade. Devido à importância deste assunto, decidi focar a minha tese de mestrado neste assunto. Sendo assim foi feita uma pesquisa bibliográfica de forma a tentar entender o problema em mãos e ainda a execução de um algoritmo capaz de ajudar a resolver este problema.Diabetes Mellitus is a serious global problem that is growing exponentially over the years all over the world, both in developed countries and in developing countries. This condition has effects throughout the body and on the eye level the most disturbing disease is diabetic retinopathy, since it can lead to blindness. This condition is detected only from certain medical tests and no symptomsare detected until the disease is in a very advanced state. The Diabetic Retinopathy has various clinical stages, which are defined by different ophthalmic features found in the retinal fundus images. The microaneurysms are the first features to appear, followed by hemorrhages and exudates. Progression of the disease leads to a more advanced stage in which arises ischemia culminating in the growth of new blood vessels. The treatment goes primarily by prevention through careful monitoring in patients with diabetes, who have their eyes examined at least once a year. In later stages it has to resort to laser treatments. As these techniques do not fully recover the prevention vision is very important the automation of screening processes. This is a subject of growing and highly importance to society. Because of the importance of this subject, I decided to focus my master's thesis on this subject. Thus it was made a literature search in order to try to understand the problem at hand and even the execution of an algorithm able to help solve this problem