most citedOpto-UNet: Optimized UNet for Segmentation of Varicose Veins in Optical Coherence Tomography

10 citations · 17 across the 5 of their papers we have counts for

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5 papers

physics.optics20252 cited

Reconstruction of Optical Coherence Tomography Images from Wavelength-space Using Deep-learning

Maryam Viqar, Erdem Sahin, Elena Stoykova +1

Conventional Fourier-domain Optical Coherence Tomography (FD-OCT) systems depend on resampling into wavenumber (k) domain to extract the depth profile. This either necessitates add…

eess.IV20231 cited

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…

eess.IV202310 cited

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…

cs.CV20234 cited

Frequency-domain Blind Quality Assessment of Blurred and Blocking-artefact Images using Gaussian Process Regression model

Maryam Viqar, Athar A. Moinuddin, Ekram Khan +1

Most of the standard image and video codecs are block-based and depending upon the compression ratio the compressed images/videos suffer from different distortions. At low ratios,…

eess.IV2023

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…