SAMSA 2.0: Prompting Segment Anything with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
Fuente:
arXiv
Saved in:
| Main Authors: | Roddan, Alfie, Czempiel, Tobias, Xu, Chi, Elson, Daniel S., Giannarou, Stamatia |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
SAMSA: Segment Anything Model Enhanced with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
by: Roddan, Alfie, et al.
Published: (2025)
by: Roddan, Alfie, et al.
Published: (2025)
Explainable Image Classification with Reduced Overconfidence for Tissue Characterisation
by: Roddan, Alfie, et al.
Published: (2025)
by: Roddan, Alfie, et al.
Published: (2025)
RGB to Hyperspectral: Spectral Reconstruction for Enhanced Surgical Imaging
by: Czempiel, Tobias, et al.
Published: (2024)
by: Czempiel, Tobias, et al.
Published: (2024)
Confidence-Based Annotation Of Brain Tumours In Ultrasound
by: Weld, Alistair, et al.
Published: (2025)
by: Weld, Alistair, et al.
Published: (2025)
Image Synthesis with Class-Aware Semantic Diffusion Models for Surgical Scene Segmentation
by: Zhou, Yihang, et al.
Published: (2024)
by: Zhou, Yihang, et al.
Published: (2024)
Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image Segmentation
by: Wei, Zhikai, et al.
Published: (2024)
by: Wei, Zhikai, et al.
Published: (2024)
Cross Prompting Consistency with Segment Anything Model for Semi-supervised Medical Image Segmentation
by: Miao, Juzheng, et al.
Published: (2024)
by: Miao, Juzheng, et al.
Published: (2024)
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
by: Wu, Junde, et al.
Published: (2023)
by: Wu, Junde, et al.
Published: (2023)
Enhancing the Reliability of Segment Anything Model for Auto-Prompting Medical Image Segmentation with Uncertainty Rectification
by: Zhang, Yichi, et al.
Published: (2023)
by: Zhang, Yichi, et al.
Published: (2023)
SurgPose: Generalisable Surgical Instrument Pose Estimation using Zero-Shot Learning and Stereo Vision
by: Rai, Utsav, et al.
Published: (2025)
by: Rai, Utsav, et al.
Published: (2025)
Segment Anything in Medical Images
by: Ma, Jun, et al.
Published: (2023)
by: Ma, Jun, et al.
Published: (2023)
Register Anything: Estimating "Corresponding Prompts" for Segment Anything Model
by: Huang, Shiqi, et al.
Published: (2025)
by: Huang, Shiqi, et al.
Published: (2025)
I-MedSAM: Implicit Medical Image Segmentation with Segment Anything
by: Wei, Xiaobao, et al.
Published: (2023)
by: Wei, Xiaobao, et al.
Published: (2023)
Scribble-Based Interactive Segmentation of Medical Hyperspectral Images
by: Wang, Zhonghao, et al.
Published: (2024)
by: Wang, Zhonghao, et al.
Published: (2024)
Matte Anything: Interactive Natural Image Matting with Segment Anything Models
by: Yao, Jingfeng, et al.
Published: (2023)
by: Yao, Jingfeng, et al.
Published: (2023)
A Probabilistic Segment Anything Model for Ambiguity-Aware Medical Image Segmentation
by: Ward, Tyler, et al.
Published: (2025)
by: Ward, Tyler, et al.
Published: (2025)
Segment Anything Model for Medical Images?
by: Huang, Yuhao, et al.
Published: (2023)
by: Huang, Yuhao, et al.
Published: (2023)
Omni-Fusion of Spatial and Spectral for Hyperspectral Image Segmentation
by: Zhang, Qing, et al.
Published: (2025)
by: Zhang, Qing, et al.
Published: (2025)
Learning to Prompt Segment Anything Models
by: Huang, Jiaxing, et al.
Published: (2024)
by: Huang, Jiaxing, et al.
Published: (2024)
SAMIC: Segment Anything with In-Context Spatial Prompt Engineering
by: Nagendra, Savinay, et al.
Published: (2024)
by: Nagendra, Savinay, et al.
Published: (2024)
Part-aware Prompted Segment Anything Model for Adaptive Segmentation
by: Zhao, Chenhui, et al.
Published: (2024)
by: Zhao, Chenhui, et al.
Published: (2024)
S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation
by: Paranjape, Jay N., et al.
Published: (2024)
by: Paranjape, Jay N., et al.
Published: (2024)
SAM3-Adapter: Efficient Adaptation of Segment Anything 3 for Camouflage Object Segmentation, Shadow Detection, and Medical Image Segmentation
by: Chen, Tianrun, et al.
Published: (2025)
by: Chen, Tianrun, et al.
Published: (2025)
pFedSAM: Personalized Federated Learning of Segment Anything Model for Medical Image Segmentation
by: Wang, Tong, et al.
Published: (2025)
by: Wang, Tong, et al.
Published: (2025)
SAIF: A Stability-Aware Inference Framework for Medical Image Segmentation with Segment Anything Model
by: Wu, Ke, et al.
Published: (2026)
by: Wu, Ke, et al.
Published: (2026)
SAM-REF: Introducing Image-Prompt Synergy during Interaction for Detail Enhancement in the Segment Anything Model
by: Yu, Chongkai, et al.
Published: (2024)
by: Yu, Chongkai, et al.
Published: (2024)
Multi-rater Prompting for Ambiguous Medical Image Segmentation
by: Wang, Jinhong, et al.
Published: (2024)
by: Wang, Jinhong, et al.
Published: (2024)
SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
by: Xiong, Xinyu, et al.
Published: (2024)
by: Xiong, Xinyu, et al.
Published: (2024)
Segment Anything in Medical Images and Videos: Benchmark and Deployment
by: Ma, Jun, et al.
Published: (2024)
by: Ma, Jun, et al.
Published: (2024)
Benchmarking Human and Automated Prompting in the Segment Anything Model
by: Quesada, Jorge, et al.
Published: (2024)
by: Quesada, Jorge, et al.
Published: (2024)
FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
by: Tian, Yu, et al.
Published: (2023)
by: Tian, Yu, et al.
Published: (2023)
Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directions
by: Zhang, Yichi, et al.
Published: (2024)
by: Zhang, Yichi, et al.
Published: (2024)
DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation
by: Gao, Yifan, et al.
Published: (2023)
by: Gao, Yifan, et al.
Published: (2023)
Dynamic Prompt Generation for Interactive 3D Medical Image Segmentation Training
by: Ndir, Tidiane Camaret, et al.
Published: (2025)
by: Ndir, Tidiane Camaret, et al.
Published: (2025)
Matching Anything by Segmenting Anything
by: Li, Siyuan, et al.
Published: (2024)
by: Li, Siyuan, et al.
Published: (2024)
Skip and Skip: Segmenting Medical Images with Prompts
by: Chen, Jiawei, et al.
Published: (2024)
by: Chen, Jiawei, et al.
Published: (2024)
Depthwise-Dilated Convolutional Adapters for Medical Object Tracking and Segmentation Using the Segment Anything Model 2
by: Xu, Guoping, et al.
Published: (2025)
by: Xu, Guoping, et al.
Published: (2025)
Annotation-Efficient Task Guidance for Medical Segment Anything
by: Ward, Tyler, et al.
Published: (2024)
by: Ward, Tyler, et al.
Published: (2024)
PP-SAM: Perturbed Prompts for Robust Adaptation of Segment Anything Model for Polyp Segmentation
by: Rahman, Md Mostafijur, et al.
Published: (2024)
by: Rahman, Md Mostafijur, et al.
Published: (2024)
EP-SAM: Weakly Supervised Histopathology Segmentation via Enhanced Prompt with Segment Anything
by: Song, Joonhyeon, et al.
Published: (2024)
by: Song, Joonhyeon, et al.
Published: (2024)
Similar Items
-
SAMSA: Segment Anything Model Enhanced with Spectral Angles for Hyperspectral Interactive Medical Image Segmentation
by: Roddan, Alfie, et al.
Published: (2025) -
Explainable Image Classification with Reduced Overconfidence for Tissue Characterisation
by: Roddan, Alfie, et al.
Published: (2025) -
RGB to Hyperspectral: Spectral Reconstruction for Enhanced Surgical Imaging
by: Czempiel, Tobias, et al.
Published: (2024) -
Confidence-Based Annotation Of Brain Tumours In Ultrasound
by: Weld, Alistair, et al.
Published: (2025) -
Image Synthesis with Class-Aware Semantic Diffusion Models for Surgical Scene Segmentation
by: Zhou, Yihang, et al.
Published: (2024)