Projects of László G. Nyúl

We are researching and developing image processing algorithms for dermatological applications in diagnostic and decision making systems as well as for education. This includes the creation of a personalized surface model from a set of color and depth camera images, detection and classification of dermatological findings, such as psoriasis lesions and plaques, as well as longitudinal analysis of changes.

The aim of this project is to improve the well-known methods of continuous and discrete tomography. We study image processing methods that can be applied directly on the projections to improve reconstruction quality. We improve techniques to measure the quality of the reconstructed images, and develop image reconstruction methods based on parallel processing using GPUs. We also investigate which are the most valuable projections, if the reconstruction is performed from just a few of them.

We apply and evaluate machine learning methods to obtain information purely from the tomographic projections of an image. We design and implement discrete tomographic reconstruction methods that can exploit the knowledge obtained in this way.

Methods for the automatic detection and evaluation of Glaucoma and other eye diseases from screening examinations.

Study and development of image segmentation algorithms for different organs from CT images for radiotherapy planning purposes.

We developed an image processing method for MRI intensity standardization. We also introduced new, fast implementations of the fuzzy connectedness algorithm that allows segmentation at interactive speeds. We developed a new segmentation "workshop" for brain MRI segmentation using standardized MR images and the fast fuzzy connectedness algorithms.