2 citations · 4 across the 10 of their papers we have counts for
4 papers · 1 filter
Federated Black-Box Adaptation for Semantic Segmentation
Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula +1
Federated Learning (FL) is a form of distributed learning that allows multiple institutions or clients to collaboratively learn a global model to solve a task. This allows the mode…
S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation
Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula +1
Medical image segmentation has been traditionally approached by training or fine-tuning the entire model to cater to any new modality or dataset. However, this approach often requi…
Blackbox Adaptation for Medical Image Segmentation
Jay N. Paranjape, Shameema Sikder, S. Swaroop Vedula +1
In recent years, various large foundation models have been proposed for image segmentation. There models are often trained on large amounts of data corresponding to general compute…
An Endoscopic Chisel: Intraoperative Imaging Carves 3D Anatomical Models
Jan Emily Mangulabnan, Roger D. Soberanis-Mukul, Timo Teufel +7
Purpose: Preoperative imaging plays a pivotal role in sinus surgery where CTs offer patient-specific insights of complex anatomy, enabling real-time intraoperative navigation to co…