75 citations · 342 across the 18 of their papers we have counts for
7 papers · 1 filter
A Multimodal Approach for Fluid Overload Prediction: Integrating Lung Ultrasound and Clinical Data
Tianqi Yang, Nantheera Anantrasirichai, Oktay Karakuş +2
Managing fluid balance in dialysis patients is crucial, as improper management can lead to severe complications. In this paper, we propose a multimodal approach that integrates vis…
CPSNet: Physics-Inspired Label-Free Deep Unfolding for Lung Ultrasound B-Line Detection
Tianqi Yang, Oktay Karakuş, Nantheera Anantrasirichai +2
In this paper, we propose CPSNet, a label-free deep unfolding framework for lung ultrasound image analysis. CPSNet unfolds a Cauchy proximal splitting algorithm into a forward-back…
DUBLINE: A Deep Unfolding Network for B-line Detection in Lung Ultrasound Images
Tianqi Yang, Nantheera Anantrasirichai, Oktay Karakuş +3
In the context of lung ultrasound, the detection of B-lines, which are indicative of interstitial lung disease and pulmonary edema, plays a pivotal role in clinical diagnosis. Curr…
Exploiting the Dual-Tree Complex Wavelet Transform for Ship Wake Detection in SAR Imagery
Wanli Ma, Alin Achim, Oktay Karakuş
In this paper, we analyse synthetic aperture radar (SAR) images of the sea surface using an inverse problem formulation whereby Radon domain information is enhanced in order to acc…
A Simulation Study to Evaluate the Performance of the Cauchy Proximal Operator in Despeckling SAR Images of the Sea Surface
Oktay Karakuş, Igor Rizaev, Alin Achim
The analysis of ocean surface is widely performed using synthetic aperture radar (SAR) imagery as it yields information for wide areas under challenging weather conditions, during…
A Generalized Gaussian Extension to the Rician Distribution for SAR Image Modeling
Oktay Karakuş, Ercan E. Kuruoglu, Alin Achim
In this paper, we present a novel statistical model, (GG-Rician) distribution, for the characterization of synthetic aperture radar (SAR)…
Detection of Line Artefacts in Lung Ultrasound Images of COVID-19 Patients via Non-Convex Regularization
Oktay Karakuş, Nantheera Anantrasirichai, Amazigh Aguersif +3
In this paper, we present a novel method for line artefacts quantification in lung ultrasound (LUS) images of COVID-19 patients. We formulate this as a non-convex regularisation pr…