19 research outputs found
Segmentation of Retinal Low-Cost Optical Coherence Tomography Images using Deep Learning
The treatment of age-related macular degeneration (AMD) requires continuous
eye exams using optical coherence tomography (OCT). The need for treatment is
determined by the presence or change of disease-specific OCT-based biomarkers.
Therefore, the monitoring frequency has a significant influence on the success
of AMD therapy. However, the monitoring frequency of current treatment schemes
is not individually adapted to the patient and therefore often insufficient.
While a higher monitoring frequency would have a positive effect on the success
of treatment, in practice it can only be achieved with a home monitoring
solution. One of the key requirements of a home monitoring OCT system is a
computer-aided diagnosis to automatically detect and quantify pathological
changes using specific OCT-based biomarkers. In this paper, for the first time,
retinal scans of a novel self-examination low-cost full-field OCT (SELF-OCT)
are segmented using a deep learning-based approach. A convolutional neural
network (CNN) is utilized to segment the total retina as well as pigment
epithelial detachments (PED). It is shown that the CNN-based approach can
segment the retina with high accuracy, whereas the segmentation of the PED
proves to be challenging. In addition, a convolutional denoising autoencoder
(CDAE) refines the CNN prediction, which has previously learned retinal shape
information. It is shown that the CDAE refinement can correct segmentation
errors caused by artifacts in the OCT image.Comment: Accepted for SPIE Medical Imaging 2020: Computer-Aided Diagnosi
On solving systems of differential algebraic equations
summary:In the paper the comparison method is used to prove the convergence of the Picard iterations, the Seidel iterations, as well as some modifications of these methods applied to approximate solution of systems of differential algebraic equations. The both linear and nonlinear comparison equations are emloyed