Cover Image

Staged Voxel-Level Deep Reinforcement Learning for 3D Medical Image Segmentation with Noisy Annotations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fu, Yuyang, Guo, Xiuzhen, Shi, Ji
Format:	Preprint
Published:	2026
Subjects:	Image and Video 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

The Effect of Lossy Compression on 3D Medical Images Segmentation with Deep Learning
by: Kurmukov, Anvar, et al.
Published: (2024)

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

DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling
by: Ji, Hangyu
Published: (2025)

Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation
by: Lin, Yi, et al.
Published: (2025)

3D Medical Imaging Segmentation on Non-Contrast CT
by: Gang, Canxuan, et al.
Published: (2025)

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

Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware Learning
by: Jiang, Runmin, et al.
Published: (2024)

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

Evaluation of Extra Pixel Interpolation with Mask Processing for Medical Image Segmentation with Deep Learning
by: Rukundo, Olivier
Published: (2023)

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

Deep Generative Models for 3D Medical Image Synthesis
by: Friedrich, Paul, et al.
Published: (2024)

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

TBConvL-Net: A Hybrid Deep Learning Architecture for Robust Medical Image Segmentation
by: Iqbal, Shahzaib, et al.
Published: (2024)

Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation
by: Płotka, Szymon, et al.
Published: (2024)

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation
by: Gang, Canxuan
Published: (2025)

FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images
by: Shen, Yiqing, et al.
Published: (2024)

M3DA: Benchmark for Unsupervised Domain Adaptation in 3D Medical Image Segmentation
by: Shirokikh, Boris, et al.
Published: (2025)

Tyche: Stochastic In-Context Learning for Medical Image Segmentation
by: Rakic, Marianne, et al.
Published: (2024)

SGDC: Structurally-Guided Dynamic Convolution for Medical Image Segmentation
by: Shi, Bo, et al.
Published: (2026)

3D-EffiViTCaps: 3D Efficient Vision Transformer with Capsule for Medical Image Segmentation
by: Gan, Dongwei, et al.
Published: (2024)

Structure Unbiased Adversarial Model for Medical Image Segmentation
by: Zhang, Tianyang, et al.
Published: (2022)

Vision-Language Controlled Deep Unfolding for Joint Medical Image Restoration and Segmentation
by: Chen, Ping, et al.
Published: (2026)

Mutual Evidential Deep Learning for Medical Image Segmentation
by: He, Yuanpeng, et al.
Published: (2025)

Segment Anything in Medical Images
by: Ma, Jun, et al.
Published: (2023)

Comprehensive Review of Reinforcement Learning for Medical Ultrasound Imaging
by: Elmekki, Hanae, et al.
Published: (2025)

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

DB-SAM: Delving into High Quality Universal Medical Image Segmentation
by: Qin, Chao, et al.
Published: (2024)

Are Vision xLSTM Embedded UNet More Reliable in Medical 3D Image Segmentation?
by: Dutta, Pallabi, et al.
Published: (2024)

MLRU++: Multiscale Lightweight Residual UNETR++ with Attention for Efficient 3D Medical Image Segmentation
by: Yadav, Nand Kumar, et al.
Published: (2025)

On The Robustness of Foundational 3D Medical Image Segmentation Models Against Imprecise Visual Prompts
by: Chattopadhyay, Soumitri, et al.
Published: (2026)

Harnessing Lightweight Transformer with Contextual Synergic Enhancement for Efficient 3D Medical Image Segmentation
by: Liu, Xinyu, et al.
Published: (2026)

Distillation Learning Guided by Image Reconstruction for One-Shot Medical Image Segmentation
by: Zhou, Feng, et al.
Published: (2024)

MS-Twins: Multi-Scale Deep Self-Attention Networks for Medical Image Segmentation
by: Xu, Jing
Published: (2023)

Deep Learning in Medical Image Registration: Magic or Mirage?
by: Jena, Rohit, et al.
Published: (2024)

Beyond Point Annotation: A Weakly Supervised Network Guided by Multi-Level Labels Generated from Four-Point Annotation for Thyroid Nodule Segmentation in Ultrasound Image
by: Chi, Jianning, et al.
Published: (2024)

Segmenting Medical Images with Limited Data
by: Liua, Zhaoshan, et al.
Published: (2024)

Bridging the Inter-Domain Gap through Low-Level Features for Cross-Modal Medical Image Segmentation
by: Lyu, Pengfei, et al.
Published: (2025)

Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images
by: Javed, Syed, et al.
Published: (2024)

Enhancing Medical Image Segmentation with Deep Learning and Diffusion Models
by: Liu, Houze, et al.
Published: (2024)

GASA-UNet: Global Axial Self-Attention U-Net for 3D Medical Image Segmentation
by: Sun, Chengkun, et al.
Published: (2024)