6 papers
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…
Confidence-Based Annotation Of Brain Tumours In Ultrasound
Alistair Weld, Luke Dixon, Alfie Roddan +3
Purpose: An investigation of the challenge of annotating discrete segmentations of brain tumours in ultrasound, with a focus on the issue of aleatoric uncertainty along the tumour…
Explainable Image Classification with Reduced Overconfidence for Tissue Characterisation
Alfie Roddan, Chi Xu, Serine Ajlouni +3
The deployment of Machine Learning models intraoperatively for tissue characterisation can assist decision making and guide safe tumour resections. For image classification models,…
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…
SurgRIPE challenge: Benchmark of Surgical Robot Instrument Pose Estimation
Haozheng Xu, Alistair Weld, Chi Xu +16
Accurate instrument pose estimation is a crucial step towards the future of robotic surgery, enabling applications such as autonomous surgical task execution. Vision-based methods…
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…