We are pleased to announce that Lesław Pawlaczyk (CEO) has written an article which will be presented in a prestigious international conference FedCSIS 2025 (https://2025.fedcsis.org/). The article is titled 'Hybrid U-Net segmentation of vessels in fundus eye images' and it talks about a novel segmentation approach to vessels on fundus eye images. This technology is being used in our products. The abstract is shown below:
We present a novel multi-stage method for colour image segmentation, with a primary focus on vessels segmentation in retinal fundus images, using a U-Net based architecture. Our approach tackles challenges posed by varying image resolutions through a coarse-to-fine segmentation pipeline. It begins with a rough segmentation at varying scales, guided by a traditional CNN and progressively refines results to find a target resolution. It culminates with detailed segmentation at a target scale with a smaller window sliding step, compared to previous stages. We train and validate our method using four publicly available datasets FIVES, DRHAGIS, HRF, and STARE - and demonstrate superior performance compared to traditional sliding window techniques. Notably, our model achieves high accuracy with relatively few training images. The entire framework is opensourced and adaptable to a wide range of image segmentation tasks.
This is in line with our broader strategy of publishing scientific papers in the field of ophthalmology and AI. In the coming months, we will inform about further articles.
