Renátó Besenczi

A review on automatic analysis techniques for color fundus photographs.

In this paper, we give a review on automatic image processing tools to recognize diseases causing specific distortions in the human retina. After a brief summary of the biology of the retina, we give an overview of the types of lesions that may appear as biomarkers of both eye and non-eye diseases. We present several state-of-the-art procedures to extract the anatomic components and lesions in color fundus photographs and decision support methods to help clinical diagnosis. We list publicly available databases and appropriate measurement techniques to compare quantitatively the performance of these approaches. Furthermore, we discuss on how the performance of image processing-based systems can be improved by fusing the output of individual detector algorithms. Retinal image analysis using mobile phones is also addressed as an expected future trend in this field.

OOCWC: The robocar world championship initiative

Robocar World Championship or briefly OOCWC is a new initiative to create a community of people who share their interest in investigating the relationship between smart cities and robot cars with particular attention to the spread of robot cars in the near future. At the heart of this initiative is the Robocar City Emulator. It is intended to offer a common research platform for the investigation of the smart city simulations. In this paper, we review the recent advances of OOCWC.

Measuring regularity of network patterns by grid approximations using the LLL algorithm

In a recent work, we have proposed a novel way to approximate point sets with grids using the LLL algorithm, which operates in polynomial time. Now, we show how this approach can be applied to pattern recognition purposes with interpreting the rate of approximation as a new feature for regularity measurement. Our practical problem is the characterization of pigment networks in skin lesions. For this task we also introduce a novel image processing method for the extraction of the pigment network. Then, we show how our grid approximation framework can be applied with specializing it for the recognition of hexagonal patterns. The classification performance of our approach for the pigment network characterization problem is measured on a database annotated by a clinical expert. Throughout the paper we address several practical issues that may help to apply our general framework to other practical tasks, as well.

Automatic optic disc and optic cup detection in retinal images acquired by mobile phone

Medical image processing plays an important role in the automatic detection of certain eye diseases, disease documentation, treatment monitoring and educational purposes. The continuous improvement of the hardware of mobile phones gives us the ability to capture images like this. Interesting question can be: are these images suitable for automatic image processing, or more specifically, how much information can be obtained from this kind of images? In this paper, we would like to investigate whether a mobile device suitable to use as a medical diagnostic tool. We present a comparison between images made by a mobile device and a clinical eye examination one. We perform optic disc and optic cup detection from which we calculate cup to disc ratio. Our results show that images acquired by mobile phone are suitable for automatic image processing. Beyond these, a database of images were set up to allow researchers to test their algorithms and methods for image processing.