Cover Image

MorphSAM: Learning the Morphological Prompts from Atlases for Spine Image Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fan, Dingwei, Zhao, Junyong, Li, Chunlin, Wang, Mingliang, Zhu, Qi, Si, Haipeng, Zhang, Daoqiang, Sun, Liang
Format:	Preprint
Published:	2025
Subjects:	Image and Video Processing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Gland Segmentation Using SAM With Cancer Grade as a Prompt
by: Zhu, Yijie, et al.
Published: (2025)

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

Optimizing Prompt Strategies for SAM: Advancing lesion Segmentation Across Diverse Medical Imaging Modalities
by: Wang, Yuli, et al.
Published: (2024)

PA-SAM: Prompt Adapter SAM for High-Quality Image Segmentation
by: Xie, Zhaozhi, et al.
Published: (2024)

K-SAM: A Prompting Method Using Pretrained U-Net to Improve Zero Shot Performance of SAM on Lung Segmentation in CXR Images
by: Deriche, Mohamed, et al.
Published: (2024)

Human Gaze-based Dual Teacher Guidance Learning for Semi-Supervised Medical Image Segmentation
by: Ge, Rongjun, et al.
Published: (2026)

UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images
by: Chen, Zhen, et al.
Published: (2024)

SpinalSAM-R1: A Vision-Language Multimodal Interactive System for Spine CT Segmentation
by: Liu, Jiaming, et al.
Published: (2025)

PathSeqSAM: Sequential Modeling for Pathology Image Segmentation with SAM2
by: Zhu, Mingyang, et al.
Published: (2025)

Morphological Reconstruction of Detached Dendritic Spines via Geodesic Path Prediction
by: Jain, Sammit, et al.
Published: (2020)

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

MBA-Net: SAM-driven Bidirectional Aggregation Network for Ovarian Tumor Segmentation
by: Gao, Yifan, et al.
Published: (2024)

Adapting SAM for Surgical Instrument Tracking and Segmentation in Endoscopic Submucosal Dissection Videos
by: Yu, Jieming, et al.
Published: (2024)

Diffusion-empowered AutoPrompt MedSAM
by: Huang, Peng, et al.
Published: (2025)

SpineFM: Leveraging Foundation Models for Automatic Spine X-ray Segmentation
by: Simons, Samuel J., et al.
Published: (2024)

Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images
by: Tu, Zhengzheng, et al.
Published: (2024)

MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for Echocardiography
by: Kim, Sekeun, et al.
Published: (2023)

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

Lumbar Spine Tumor Segmentation and Localization in T2 MRI Images Using AI
by: Pal, Rikathi, et al.
Published: (2024)

A Dual-Feature Extractor Framework for Accurate Back Depth and Spine Morphology Estimation from Monocular RGB Images
by: Wei, Yuxin, et al.
Published: (2025)

Building Lightweight Semantic Segmentation Models for Aerial Images Using Dual Relation Distillation
by: Li, Minglong, et al.
Published: (2025)

Prompt-based Multimodal Semantic Communication for Multi-spectral Image Segmentation
by: Zhang, Haoshuo, et al.
Published: (2025)

Channel-Adaptive Wireless Image Semantic Transmission with Learnable Prompts
by: Zhang, Liang, et al.
Published: (2024)

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

Gaze-Assisted Human-Centric Domain Adaptation for Cardiac Ultrasound Image Segmentation
by: Li, Ruiyi, et al.
Published: (2025)

SemiSAM+: Rethinking Semi-Supervised Medical Image Segmentation in the Era of Foundation Models
by: Zhang, Yichi, et al.
Published: (2025)

Attack and Defense Analysis of Learned Image Compression
by: Zhu, Tianyu, et al.
Published: (2024)

SpineMamba: Enhancing 3D Spinal Segmentation in Clinical Imaging through Residual Visual Mamba Layers and Shape Priors
by: Zhang, Zhiqing, et al.
Published: (2024)

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

One-Prompt to Segment All Medical Images
by: Wu, Junde, et al.
Published: (2023)

SpeHeatal: A Cluster-Enhanced Segmentation Method for Sperm Morphology Analysis
by: Shi, Yi, et al.
Published: (2025)

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

SegX: Improving Interpretability of Clinical Image Diagnosis with Segmentation-based Enhancement
by: Zhang, Yuhao, et al.
Published: (2025)

Rethinking Few-Shot Medical Image Segmentation by SAM2: A Training-Free Framework with Augmentative Prompting and Dynamic Matching
by: Zu, Haiyue, et al.
Published: (2025)

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

Challenge Summary U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation
by: Wang, Xin, et al.
Published: (2024)

Semantics Guided Disentangled GAN for Chest X-ray Image Rib Segmentation
by: Huang, Lili, et al.
Published: (2024)

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

CRC-SAM: SAM-Based Multi-Modal Segmentation and Quantification of Colorectal Cancer in CT, Colonoscopy, and Histology Images
by: Lao, Daniel
Published: (2026)

Morphological-consistent Diffusion Network for Ultrasound Coronal Image Enhancement
by: Zhou, Yihao, et al.
Published: (2024)