Cover Image

SegmentAnyMuscle: A universal muscle segmentation model across different locations in MRI

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Colglazier, Roy, Lee, Jisoo, Dong, Haoyu, Gu, Hanxue, Chen, Yaqian, Cao, Joseph, Yildiz, Zafer, Liu, Zhonghao, Konz, Nicholas, Yang, Jichen, Zhang, Jikai, Chen, Yuwen, Li, Lin, Camarena, Adrian, Mazurowski, Maciej A.
Format:	Preprint
Published:	2025
Subjects:	Signal Processing Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Accelerating Volumetric Medical Image Annotation via Short-Long Memory SAM 2
by: Chen, Yuwen, et al.
Published: (2025)

Automated Muscle and Fat Segmentation in Computed Tomography for Comprehensive Body Composition Analysis
by: Chen, Yaqian, et al.
Published: (2025)

MRI-CORE: A Foundation Model for Magnetic Resonance Imaging
by: Dong, Haoyu, et al.
Published: (2025)

ContourDiff: Unpaired Medical Image Translation with Structural Consistency
by: Chen, Yuwen, et al.
Published: (2024)

SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI
by: Gu, Hanxue, et al.
Published: (2024)

GuidedMorph: Two-Stage Deformable Registration for Breast MRI
by: Chen, Yaqian, et al.
Published: (2025)

Segment anything model 2: an application to 2D and 3D medical images
by: Dong, Haoyu, et al.
Published: (2024)

Rethinking Perceptual Metrics for Medical Image Translation
by: Konz, Nicholas, et al.
Published: (2024)

LegSegNet: A Public Deep Learning System for Lower Extremity CT Tissue Segmentation and Quantification
by: Chen, Yuwen, et al.
Published: (2026)

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

How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model
by: Gu, Hanxue, et al.
Published: (2024)

BreastSegNet: Multi-label Segmentation of Breast MRI
by: Li, Qihang, et al.
Published: (2025)

Medical Image Segmentation with InTEnt: Integrated Entropy Weighting for Single Image Test-Time Adaptation
by: Dong, Haoyu, et al.
Published: (2024)

Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?
by: Gu, Hanxue, et al.
Published: (2025)

Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models
by: Konz, Nicholas, et al.
Published: (2024)

Improving Surgical Risk Prediction Through Integrating Automated Body Composition Analysis: a Retrospective Trial on Colectomy Surgery
by: Gu, Hanxue, et al.
Published: (2025)

Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completion
by: Konz, Nicholas, et al.
Published: (2023)

The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images
by: Konz, Nicholas, et al.
Published: (2024)

Pre-processing and Compression: Understanding Hidden Representation Refinement Across Imaging Domains via Intrinsic Dimension
by: Konz, Nicholas, et al.
Published: (2024)

Deep Learning for Breast MRI Style Transfer with Limited Training Data
by: Cao, Shixing, et al.
Published: (2023)

Effectiveness of Automatically Curated Dataset in Thyroid Nodules Classification Algorithms Using Deep Learning
by: Yang, Jichen, et al.
Published: (2026)

Breast density in MRI: an AI-based quantification and relationship to assessment in mammography
by: Chen, Yaqian, et al.
Published: (2025)

Transplant-Ready? Evaluating AI Lung Segmentation Models in Candidates with Severe Lung Disease
by: Lee, Jisoo, et al.
Published: (2025)

Quantifying the Limits of Segmentation Foundation Models: Modeling Challenges in Segmenting Tree-Like and Low-Contrast Objects
by: Zhang, Yixin, et al.
Published: (2024)

How to Efficiently Annotate Images for Best-Performing Deep Learning Based Segmentation Models: An Empirical Study with Weak and Noisy Annotations and Segment Anything Model
by: Zhang, Yixin, et al.
Published: (2023)

Fully Automated Deep Learning Based Glenoid Bone Loss Measurement and Severity Stratification on 3D CT in Shoulder Instability
by: Liu, Zhonghao, et al.
Published: (2025)

Deep learning automates Cobb angle measurement compared with multi-expert observers
by: Li, Keyu, et al.
Published: (2024)

Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets
by: Konz, Nicholas, et al.
Published: (2024)

How to select slices for annotation to train best-performing deep learning segmentation models for cross-sectional medical images?
by: Zhang, Yixin, et al.
Published: (2024)

The Impact of Scanner Domain Shift on Deep Learning Performance in Medical Imaging: an Experimental Study
by: Guo, Brian, et al.
Published: (2024)

Convolutional Neural Networks Rarely Learn Shape for Semantic Segmentation
by: Zhang, Yixin, et al.
Published: (2023)

The Antiviral Effect of Two Important Base Analogs, Ribavirin and 5‐Fluoruracil, on Infectious Pancreatic Necrosis Virus
by: Yasemin Çiçek Yıldız, et al.
Published: (2024)

A multiscale feature fusion‐guided lightweight semantic segmentation network
by: Xin Ye, et al.
Published: (2024)

Dereflection Any Image with Diffusion Priors and Diversified Data
by: Hu, Jichen, et al.
Published: (2025)

Diagnostic Impact of Cine Clips for Thyroid Nodule Assessment on Ultrasound
by: Yang, Jichen, et al.
Published: (2026)

Language Models and Retrieval Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports
by: Jabal, Mohamed Sobhi, et al.
Published: (2024)

Kunst im Religionsunterricht – Empirische Erkundungen heterogenitätssensibler Lernprozesse
by: Gärtner, Claudia, et al.
Published: (2025)

Changes in the Expression of Some Genes With Metabolic, VLDL and Antioxidative Effects After the Addition of Essential Oil Mixture to Drinking Water in the Liver of Domestic Geese ( Anser anser Domesticus )
by: Özlem Durna, et al.
Published: (2025)

SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data
by: Wielgosz, Maciej, et al.
Published: (2024)

AnyAD: Unified Any-Modality Anomaly Detection in Incomplete Multi-Sequence MRI
by: Wu, Changwei, et al.
Published: (2025)