SEGMENTASI MICROANEURYSM PADA CITRA FUNDUS RETINA UNTUK DETEKSI DINI DIABETIC RETINOPATHY

Abstrak. Diabetik Retinopathy(DR) merupakan kelainan retina akibat dari komplikasi diabetesyang menyebabkan kebutaan. kondisi ini yang dikenal sebagai diabetik retinopati. Salah satucara untuk mengetahui bahwa ada diabetik retinopati dapat dilihat dari adanya kemunculanmicroaneurysm pada retina yang bisa dilihat melalui alat kedokteran kamera fundus. Penelitian inimengajukan suatu langkah untuk segmentasi microaneurysm pada citra retina untuk deteksi secaradini diabetik retinopati. Tahaan dalam penelitian ini adalah me-resize ulang citra, transformasi rgbke red channel, rekonstruksi morfologi, kemudian memperbaiki citra tersebut dengan contrastenhancement. Microaneurysm (MA) dideteksi dengan menggunakan filter Laplacian of gaussian.Area MA diperjelas dengan menggunakan tophat filtering, kemudian tahap terakhir dalamsegmentasi menggunakan thresholding.Kata Kunci: Diabetik Retinopati,citra fundus,deteksi microaneurysm,metode morfologi,Laplacianof gaussian, thresholding

An Improved Image Segmentation System: A Cooperative Multi-agent Strategy for 2D/3D Medical Images

In this paper, we present a solution-based cooperation approach for strengthening the image segmentation.This paper proposes a cooperative method relying on Multi-Agent System. The main contribution of this work is to highlight the importance of cooperation between the contour and region growing based on Multi-Agent System (MAS). Consequently, agents’ interactions form the main part of the whole process for image segmentation. Similar works were proposed to evaluate the effectiveness of the proposed solution. The main difference is that our Multi-Agent System can perform the segmentation process ensuring efficiency. Our results show that the performance indices in the system were higher. Furthermore, the integration of thecooperation paradigm allows to speed up the segmentation process. Besides, the tests reveal the robustness of our method by proving competitive results. Our proposal achieved an accuracy of 93,51%± 0,8, a sensitivity of 93,53%± 5,08 and a specificity rate of 92,64%± 4,01

Using a multi-agent system approach for microaneurysm detection in fundus images

Author's personal copyObjective Microaneurysms represent the first sign of diabetic retinopathy, and their detection is fundamental for the prevention of vision impairment. Despite several research attempts to develop an automated system to detect microaneurysms in fundus images, none has shown the level of performance required for clinical practice. We propose a new approach, based on a multi-agent system model, for microaneurysm segmentation. Methods and materials A multi-agent based approach, preceded by a preprocessing phase to allow construction of the environment in which agents are situated and interact, is presented. The proposed method is applied to two available online datasets and results are compared to other previously described approaches. Results Microaneurysm segmentation emerges from agent interaction. The final score of the proposed approach was 0.240 in the Retinopathy Online Challenge. Conclusions We achieved competitive results, primarily in detecting microaneurysms close to vessels, compared to more conventional algorithms. Despite these results not being optimum, they are encouraging and reveal that some improvements may be made.Fundação para a Ciência e a Tecnologia (FCT