2 papers
physics.med-ph2026
Real-time, inline quantitative MRI enabled by scanner-integrated machine learning: a proof of principle with NODDI
Samuel Rot, Iulius Dragonu, Christina Triantafyllou +11
Purpose: The clinical feasibility and translation of many advanced quantitative MRI (qMRI) techniques are inhibited by their restriction to 'research mode', due to resource-intensi…
cs.CV2024
DARES: Depth Anything in Robotic Endoscopic Surgery with Self-supervised Vector-LoRA of the Foundation Model
Mona Sheikh Zeinoddin, Chiara Lena, Jiongqi Qu +11
Robotic-assisted surgery (RAS) relies on accurate depth estimation for 3D reconstruction and visualization. While foundation models like Depth Anything Models (DAM) show promise, d…