Exploiting the Segment Anything Model (SAM) for Lung Segmentation in Chest X-ray Images
Fuente:
arXiv
Saved in:
| Main Authors: | de Carvalho, Gabriel Bellon, Almeida, Jurandy |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation
by: Gao, Yifan, et al.
Published: (2023)
by: Gao, Yifan, et al.
Published: (2023)
SAM3D: Segment Anything Model in Volumetric Medical Images
by: Bui, Nhat-Tan, et al.
Published: (2023)
by: Bui, Nhat-Tan, et al.
Published: (2023)
Hierarchical SegNet with Channel and Context Attention for Accurate Lung Segmentation in Chest X-ray Images
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024)
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024)
SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model
by: Chan, Trevor J., et al.
Published: (2024)
by: Chan, Trevor J., et al.
Published: (2024)
SAM-I2I: Unleash the Power of Segment Anything Model for Medical Image Translation
by: Huo, Jiayu, et al.
Published: (2024)
by: Huo, Jiayu, et al.
Published: (2024)
RobustSAM: Segment Anything Robustly on Degraded Images
by: Chen, Wei-Ting, et al.
Published: (2024)
by: Chen, Wei-Ting, et al.
Published: (2024)
FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images
by: Shen, Yiqing, et al.
Published: (2024)
by: Shen, Yiqing, et al.
Published: (2024)
Segment Anything in Medical Images
by: Ma, Jun, et al.
Published: (2023)
by: Ma, Jun, et al.
Published: (2023)
nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance
by: Li, Yunxiang, et al.
Published: (2023)
by: Li, Yunxiang, et al.
Published: (2023)
MoSAM: Motion-Guided Segment Anything Model with Spatial-Temporal Memory Selection
by: Yang, Qiushi, et al.
Published: (2025)
by: Yang, Qiushi, et al.
Published: (2025)
Segment Anything Model for Brain Tumor Segmentation
by: Zhang, Peng, et al.
Published: (2023)
by: Zhang, Peng, 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)
ASPS: Augmented Segment Anything Model for Polyp Segmentation
by: Li, Huiqian, et al.
Published: (2024)
by: Li, Huiqian, et al.
Published: (2024)
SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model
by: Zhang, Dingyuan, et al.
Published: (2023)
by: Zhang, Dingyuan, et al.
Published: (2023)
PathSeqSAM: Sequential Modeling for Pathology Image Segmentation with SAM2
by: Zhu, Mingyang, et al.
Published: (2025)
by: Zhu, Mingyang, et al.
Published: (2025)
Is SAM 2 Better than SAM in Medical Image Segmentation?
by: Sengupta, Sourya, et al.
Published: (2024)
by: Sengupta, Sourya, et al.
Published: (2024)
MedSAM2: Segment Anything in 3D Medical Images and Videos
by: Ma, Jun, et al.
Published: (2025)
by: Ma, Jun, et al.
Published: (2025)
Segment Anything for Histopathology
by: Griebel, Titus, et al.
Published: (2025)
by: Griebel, Titus, et al.
Published: (2025)
Prompt2SegCXR:Prompt to Segment All Organs and Diseases in Chest X-rays
by: Zami, Abduz, et al.
Published: (2025)
by: Zami, Abduz, et al.
Published: (2025)
Autoadaptive Medical Segment Anything Model
by: Ward, Tyler, et al.
Published: (2025)
by: Ward, Tyler, et al.
Published: (2025)
PA-SAM: Prompt Adapter SAM for High-Quality Image Segmentation
by: Xie, Zhaozhi, et al.
Published: (2024)
by: Xie, Zhaozhi, 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)
Adapting Segment Anything Model 3 for Concept-Driven Lesion Segmentation in Medical Images: An Experimental Study
by: Xu, Guoping, et al.
Published: (2026)
by: Xu, Guoping, et al.
Published: (2026)
Mask-Enhanced Segment Anything Model for Tumor Lesion Semantic Segmentation
by: Shi, Hairong, et al.
Published: (2024)
by: Shi, Hairong, et al.
Published: (2024)
Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images
by: Tu, Zhengzheng, et al.
Published: (2024)
by: Tu, Zhengzheng, et al.
Published: (2024)
Segment Anything Model for Medical Images?
by: Huang, Yuhao, et al.
Published: (2023)
by: Huang, Yuhao, et al.
Published: (2023)
Testing the Segment Anything Model on radiology data
by: de Almeida, José Guilherme, et al.
Published: (2023)
by: de Almeida, José Guilherme, et al.
Published: (2023)
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
by: Ma, Jun, et al.
Published: (2024)
by: Ma, Jun, et al.
Published: (2024)
fabSAM: A Farmland Boundary Delineation Method Based on the Segment Anything Model
by: Xie, Yufeng, et al.
Published: (2025)
by: Xie, Yufeng, et al.
Published: (2025)
Deshadow-Anything: When Segment Anything Model Meets Zero-shot shadow removal
by: Zhang, Xiao Feng, et al.
Published: (2023)
by: Zhang, Xiao Feng, et al.
Published: (2023)
A Novel Approach to Chest X-ray Lung Segmentation Using U-net and Modified Convolutional Block Attention Module
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024)
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024)
Unpaired Translation of Chest X-ray Images for Lung Opacity Diagnosis via Adaptive Activation Masks and Cross-Domain Alignment
by: Ning, Junzhi, et al.
Published: (2025)
by: Ning, Junzhi, et al.
Published: (2025)
Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2
by: Lou, Ange, et al.
Published: (2024)
by: Lou, Ange, et al.
Published: (2024)
OSegNet: Operational Segmentation Network for COVID-19 Detection using Chest X-ray Images
by: Degerli, Aysen, et al.
Published: (2022)
by: Degerli, Aysen, et al.
Published: (2022)
SemiSAM+: Rethinking Semi-Supervised Medical Image Segmentation in the Era of Foundation Models
by: Zhang, Yichi, et al.
Published: (2025)
by: Zhang, Yichi, et al.
Published: (2025)
Comprehensive Lung Disease Detection Using Deep Learning Models and Hybrid Chest X-ray Data with Explainable AI
by: Sarker, Shuvashis, et al.
Published: (2025)
by: Sarker, Shuvashis, et al.
Published: (2025)
SAM2-3dMed: Empowering SAM2 for 3D Medical Image Segmentation
by: Yang, Yeqing, et al.
Published: (2025)
by: Yang, Yeqing, et al.
Published: (2025)
Application of Segment Anything Model for Civil Infrastructure Defect Assessment
by: Ahmadi, Mohsen, et al.
Published: (2023)
by: Ahmadi, Mohsen, et al.
Published: (2023)
DB-SAM: Delving into High Quality Universal Medical Image Segmentation
by: Qin, Chao, et al.
Published: (2024)
by: Qin, Chao, et al.
Published: (2024)
UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images
by: Chen, Zhen, et al.
Published: (2024)
by: Chen, Zhen, et al.
Published: (2024)
Similar Items
-
DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation
by: Gao, Yifan, et al.
Published: (2023) -
SAM3D: Segment Anything Model in Volumetric Medical Images
by: Bui, Nhat-Tan, et al.
Published: (2023) -
Hierarchical SegNet with Channel and Context Attention for Accurate Lung Segmentation in Chest X-ray Images
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024) -
SAM3D: Zero-Shot Semi-Automatic Segmentation in 3D Medical Images with the Segment Anything Model
by: Chan, Trevor J., et al.
Published: (2024) -
SAM-I2I: Unleash the Power of Segment Anything Model for Medical Image Translation
by: Huo, Jiayu, et al.
Published: (2024)