1 citations · 2 across the 7 of their papers we have counts for
8 papers
HyKey: Hyperspectral Keypoint Detection and Matching in Minimally Invasive Surgery
Alexander Saikia, Chiara Di Vece, Zhehua Mao +6
Purpose: 3D reconstruction in minimally invasive surgery (MIS) enables enhanced surgical guidance through improved visualisation, tool tracking, and augmented reality. However, tra…
Current validation practice undermines surgical AI development
Annika Reinke, Ziying O. Li, Minu D. Tizabi +97
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contr…
SAMSA 2.0: Prompting Segment Anything with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
Alfie Roddan, Tobias Czempiel, Chi Xu +2
We present SAMSA 2.0, an interactive segmentation framework for hyperspectral medical imaging that introduces spectral angle prompting to guide the Segment Anything Model (SAM) usi…
SAMSA: Segment Anything Model Enhanced with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
Alfie Roddan, Tobias Czempiel, Chi Xu +2
Hyperspectral imaging (HSI) provides rich spectral information for medical imaging, yet encounters significant challenges due to data limitations and hardware variations. We introd…
MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments
Ege Özsoy, Chantal Pellegrini, Tobias Czempiel +7
Operating rooms (ORs) are complex, high-stakes environments requiring precise understanding of interactions among medical staff, tools, and equipment for enhancing surgical assista…
RGB to Hyperspectral: Spectral Reconstruction for Enhanced Surgical Imaging
Tobias Czempiel, Alfie Roddan, Maria Leiloglou +5
This study investigates the reconstruction of hyperspectral signatures from RGB data to enhance surgical imaging, utilizing the publicly available HeiPorSPECTRAL dataset from porci…