1 citations · 2 across the 4 of their papers we have counts for
4 papers
MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation
Shehan Perera, Yunus Erzurumlu, Deepak Gulati +1
Skin cancer segmentation poses a significant challenge in medical image analysis. Numerous existing solutions, predominantly CNN-based, face issues related to a lack of global cont…
SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation
Shehan Perera, Pouyan Navard, Alper Yilmaz
The adoption of Vision Transformers (ViTs) based architectures represents a significant advancement in 3D Medical Image (MI) segmentation, surpassing traditional Convolutional Neur…
Adaptive Few-Shot Learning PoC Ultrasound COVID-19 Diagnostic System
Michael Karnes, Shehan Perera, Srikar Adhikari +1
This paper presents a novel ultrasound imaging point-of-care (PoC) COVID-19 diagnostic system. The adaptive visual diagnostics utilize few-shot learning (FSL) to generate encoded d…
POCFormer: A Lightweight Transformer Architecture for Detection of COVID-19 Using Point of Care Ultrasound
Shehan Perera, Srikar Adhikari, Alper Yilmaz
The rapid and seemingly endless expansion of COVID-19 can be traced back to the inefficiency and shortage of testing kits that offer accurate results in a timely manner. An emergin…