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eess.IV2026
MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-Care Ultrasound Devices
Alvin Kimbowa, Arjun Parmar, Ibrahim Mujtaba +5
Objective: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices. Methods: We propose MonoUNet,…
eess.IV2025
Mono2D: A Trainable Monogenic Layer for Robust Knee Cartilage Segmentation on Out-of-Distribution 2D Ultrasound Data
Alvin Kimbowa, Arjun Parmar, Maziar Badii +3
Automated knee cartilage segmentation using point-of-care ultrasound devices and deep-learning networks has the potential to enhance the management of knee osteoarthritis. However,…
eess.IV2024
Wireless vs. Traditional Ultrasound Assessed Knee Cartilage Outcomes Utilizing Automated Gain and Normalization Techniques
Arjun Parmar, Corey D Grozier, Robert Dima +5
Advancements in wireless ultrasound technology allow for point of care cartilage imaging, yet validation against traditional ultrasound units remains to be established for knee car…