Automated detection of proliferative retinopathy in clinical practice

Abstract

Timely intervention for diabetic retinopathy (DR) lessens the possibility of blindness and can save considerable costs to health systems. To ensure that interventions are timely and effective requires methods of screening and monitoring pathological changes, including assessing outcomes. Fractal analysis, one method that has been studied for assessing DR, is potentially relevant in today's world of telemedicine because it provides objective indices from digital images of complex patterns such as are seen in retinal vasculature, which is affected in DR. We introduce here a protocol to distinguish between nonproliferative (NPDR) and proliferative (PDR) changes in retinal vasculature using a fractal analysis method known as local connected dimension (D conn ) analysis. The major fi nding is that compared to other fractal analysis methods, D conn analysis better differentiates NPDR from PDR (p = 0.05). In addition, we are the fi rst to show that fractal analysis can be used to differentiate between NPDR and PDR using automated vessel identifi cation. Overall, our results suggest this protocol can complement existing methods by including an automated and objective measure obtainable at a lower level of expertise that experts can then use in screening for and monitoring DR.

Quantitating the subtleties of microglial morphology with fractal analysis

“…And third, box counting software has become increasingly accessible to the neuroscience community (Karperien, 2001a; Baksi and Fidler, 2012). The reader should be aware that alternative fractal methods such as the dilation method and mass radius method have been used to characterize microglial morphology (Soltys et al, 2001; Orlowski et al, 2003; Varvel et al, 2009), and that others may prove useful (e.g., local connected fractal dimension) (Karperien, 2001a; Losa et al, 2005; Karperien et al, 2008b) but have not yet been tried.…”

“…As computerized methods of image analysis have burgeoned in the last decades, fractal analysis in neuroscience has grown to include many applications ranging from classifying neural cells to assessing diabetic retinopathy (Smith et al, 1996; Fernandez and Jelinek, 2001; Karperien et al, 2008b; Jelinek et al, 2010; Kim et al, 2011). As substantial as this body of literature is, it contains only a very small number of studies reporting on fractal analysis of microglia, many published by our lab using FracLac for ImageJ .…”

Efeito da suplementação de alimentos funcionais no músculo esquelético de ratos expostos cronicamente ao tabagismo

“…Dessa forma, a análise das lâminas histológicas fractais baseia-se na relação entre a resolução e a escala avaliada, e o resultado pode ser quantitativamente expresso como a dimensão fractal do objeto, sendo: DF= (Log Nr / log r-1), onde a Nr é a quantidade de elementos iguais necessários para preencher o objeto original e r a escala aplicada ao objeto (Figura 1). Com isso, a dimensão fractal calculada com o software Image J ficará sempre entre 0 e 2, não distinguindo texturas diferentes (KARPERIEN et al, 2008;SILVA et al, 2021).…”

A new fractal-theory-based criterion for hydrological model calibration

“…There has been spectacular growth in various areas of fractal theory and multifractal theory (Bai et al, 2019;Davis et al, 1994). According to fractal theory, fractality can be described by the Hurst exponent (rescaled range analysis) (Hurst, 1951), the Hausdorff dimension (the box-counting dimension or local dimension) (Karperien et al, 2008;Falconer, 2004) and the correlation dimension (Grassberger and Procaccia, 1983), for example. These dimensions differ in the schemes used to calculate them, but they are numerically related to and theoretically dependent on each other.…”

“…This phenomenon is also called long-term correlation, and can be described using the Hausdorff dimension (Onyutha et al, 2019). However, applications of fractal theory to simple streamflow analysis are limited and mostly only use the Hurst index (Katsev and L'Heureux, 2003). Some studies have mentioned other indices based on fractal theory (Bai et al, 2019;Zhou et al, 2014;Zhang et al, 2010) but, again, they only studied observed hydrological data.…”