10 citations · 11 across the 5 of their papers we have counts for
5 papers
WAVE-UNET: Wavelength based Image Reconstruction method using attention UNET for OCT images
Maryam Viqar, Erdem Sahin, Violeta Madjarova +2
In this work, we propose to leverage a deep-learning (DL) based reconstruction framework for high quality Swept-Source Optical Coherence Tomography (SS-OCT) images, by incorporatin…
Denoising OCT Images Using Steered Mixture of Experts with Multi-Model Inference
Aytaç Özkan, Elena Stoykova, Thomas Sikora +1
In Optical Coherence Tomography (OCT), speckle noise significantly hampers image quality, affecting diagnostic accuracy. Current methods, including traditional filtering and deep l…
Modified watershed approach for segmentation of complex optical coherence tomographic images
Maryam Viqar, Violeta Madjarova, Elena Stoykova
Watershed segmentation method has been used in various applications. But many a times, due to its over-segmentation attributes, it underperforms in several tasks where noise is a d…
Opto-UNet: Optimized UNet for Segmentation of Varicose Veins in Optical Coherence Tomography
Maryam Viqar, Violeta Madjarova, Vipul Baghel +1
Human veins are important for carrying the blood from the body-parts to the heart. The improper functioning of the human veins may arise from several venous diseases. Varicose vein…
Deep Learning based Segmentation of Optical Coherence Tomographic Images of Human Saphenous Varicose Vein
Maryam Viqar, Violeta Madjarova, Amit Kumar Yadav +2
Deep-learning based segmentation model is proposed for Optical Coherence Tomography images of human varicose vein based on the U-Net model employing atrous convolution with residua…