Imagen de Portada

FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Shen, Yiqing, Li, Jingxing, Shao, Xinyuan, Romillo, Blanca Inigo, Jindal, Ankush, Dreizin, David, Unberath, Mathias
Formato:	Preprint
Publicado:	2024
Materias:	Image and Video Processing Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification
por: Shen, Yiqing, et al.
Publicado: (2024)

Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation
por: Shen, Yiqing, et al.
Publicado: (2024)

Memorizing SAM: 3D Medical Segment Anything Model with Memorizing Transformer
por: Shao, Xinyuan, et al.
Publicado: (2024)

SAM3D: Segment Anything Model in Volumetric Medical Images
por: Bui, Nhat-Tan, et al.
Publicado: (2023)

Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIs
por: Shen, Yiqing, et al.
Publicado: (2024)

SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model
por: Chan, Trevor J., et al.
Publicado: (2024)

MedSAM2: Segment Anything in 3D Medical Images and Videos
por: Ma, Jun, et al.
Publicado: (2025)

Online Reasoning Video Segmentation with Just-in-Time Digital Twins
por: Shen, Yiqing, et al.
Publicado: (2025)

SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model
por: Zhang, Dingyuan, et al.
Publicado: (2023)

An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling
por: Inigo, Blanca, et al.
Publicado: (2024)

Comparing SAM 2 and SAM 3 for Zero-Shot Segmentation of 3D Medical Data
por: Chakrabarty, Satrajit, et al.
Publicado: (2025)

M$^4$oE: A Foundation Model for Medical Multimodal Image Segmentation with Mixture of Experts
por: Jiang, Yufeng, et al.
Publicado: (2024)

Synthetic Volumetric Data Generation Enables Zero-Shot Generalization of Foundation Models in 3D Medical Image Segmentation
por: Chakrabarty, Satrajit, et al.
Publicado: (2026)

SAM2-3dMed: Empowering SAM2 for 3D Medical Image Segmentation
por: Yang, Yeqing, et al.
Publicado: (2025)

DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation
por: Gao, Yifan, et al.
Publicado: (2023)

Operating Room Workflow Analysis via Reasoning Segmentation over Digital Twins
por: Shen, Yiqing, et al.
Publicado: (2025)

Assessing Foundational Medical 'Segment Anything' (Med-SAM1, Med-SAM2) Deep Learning Models for Left Atrial Segmentation in 3D LGE MRI
por: Mehrnia, Mehri, et al.
Publicado: (2024)

SAM & SAM 2 in 3D Slicer: SegmentWithSAM Extension for Annotating Medical Images
por: Yildiz, Zafer, et al.
Publicado: (2024)

SAM-Guided Robust Representation Learning for One-Shot 3D Medical Image Segmentation
por: Wang, Jia, et al.
Publicado: (2025)

SAM-I2I: Unleash the Power of Segment Anything Model for Medical Image Translation
por: Huo, Jiayu, et al.
Publicado: (2024)

3D Skin Segmentation Methods in Medical Imaging: A Comparison
por: Paccini, Martina, et al.
Publicado: (2025)

Conformal Lesion Segmentation for 3D Medical Images
por: Tan, Binyu, et al.
Publicado: (2025)

Efficient MedSAMs: Segment Anything in Medical Images on Laptop
por: Ma, Jun, et al.
Publicado: (2024)

Segment Anything in Medical Images
por: Ma, Jun, et al.
Publicado: (2023)

3D-U-SAM Network For Few-shot Tooth Segmentation in CBCT Images
por: Zhang, Yifu, et al.
Publicado: (2023)

SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAM
por: Liu, Yihao, et al.
Publicado: (2023)

Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directions
por: Zhang, Yichi, et al.
Publicado: (2024)

Zero-shot 3D Segmentation of Abdominal Organs in CT Scans Using Segment Anything Model 2: Adapting Video Tracking Capabilities for 3D Medical Imaging
por: Yamagishi, Yosuke, et al.
Publicado: (2024)

Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images
por: Wang, Hualiang, et al.
Publicado: (2024)

Design of 3D Non-Cartesian Trajectories for Fast Volumetric MRI via Analytic Coordinate Discretization
por: Jang, Kwang Eun, et al.
Publicado: (2025)

UNet-3D with Adaptive TverskyCE Loss for Pancreas Medical Image Segmentation
por: Zhang, Xubei, et al.
Publicado: (2025)

Volumetric Ultrasound via 3D Null Subtraction Imaging with Circular and Spiral Apertures
por: Dai, Bingze, et al.
Publicado: (2025)

Exploiting the Segment Anything Model (SAM) for Lung Segmentation in Chest X-ray Images
por: de Carvalho, Gabriel Bellon, et al.
Publicado: (2024)

RobustSAM: Segment Anything Robustly on Degraded Images
por: Chen, Wei-Ting, et al.
Publicado: (2024)

Proxy Prompt: Endowing SAM and SAM 2 with Auto-Interactive-Prompt for Medical Segmentation
por: Xinyi, Wang, et al.
Publicado: (2025)

MedContext: Learning Contextual Cues for Efficient Volumetric Medical Segmentation
por: Gani, Hanan, et al.
Publicado: (2024)

Boosting Convolution with Efficient MLP-Permutation for Volumetric Medical Image Segmentation
por: Lin, Yi, et al.
Publicado: (2023)

Autoadaptive Medical Segment Anything Model
por: Ward, Tyler, et al.
Publicado: (2025)

Skill-Evolving Grounded Reasoning for Free-Text Promptable 3D Medical Image Segmentation
por: Zhang, Tongrui, et al.
Publicado: (2026)

Is SAM 2 Better than SAM in Medical Image Segmentation?
por: Sengupta, Sourya, et al.
Publicado: (2024)