Cover Image

Foreign object segmentation in chest x-rays through anatomy-guided shape insertion

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Seibold, Constantin, Kalisch, Hamza, Heine, Lukas, Reiß, Simon, Kleesiek, Jens
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Autopet III challenge: Incorporating anatomical knowledge into nnUNet for lesion segmentation in PET/CT
by: Kalisch, Hamza, et al.
Published: (2024)

CT-GRAPH: Hierarchical Graph Attention Network for Anatomy-Guided CT Report Generation
by: Kalisch, Hamza, et al.
Published: (2025)

Region-Normalized DPO for Medical Image Segmentation under Noisy Judges
by: Kalisch, Hamza, et al.
Published: (2026)

Anatomy-guided Pathology Segmentation
by: Jaus, Alexander, et al.
Published: (2024)

De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy
by: Rempe, Moritz, et al.
Published: (2024)

Good Enough: Is it Worth Improving your Label Quality?
by: Jaus, Alexander, et al.
Published: (2025)

Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks
by: Jaus, Alexander, et al.
Published: (2024)

Automatic Fine-grained Segmentation-assisted Report Generation
by: Jonske, Frederic, et al.
Published: (2025)

Towards Synthetic Data Generation for Improved Pain Recognition in Videos under Patient Constraints
by: Nasimzada, Jonas, et al.
Published: (2024)

Cracking the PUMA Challenge in 24 Hours with CellViT++ and nnU-Net
by: Shahamiri, Negar, et al.
Published: (2025)

Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data
by: Heine, Lukas, et al.
Published: (2024)

Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?
by: Jaus, Alexander, et al.
Published: (2024)

CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models
by: Hörst, Fabian, et al.
Published: (2025)

Is Visual in-Context Learning for Compositional Medical Tasks within Reach?
by: Reiß, Simon, et al.
Published: (2025)

Learning to Look Closer: A New Instance-Wise Loss for Small Cerebral Lesion Segmentation
by: Bouteille, Luc, et al.
Published: (2025)

Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries
by: Jonske, Frederic, et al.
Published: (2023)

Frame2Freq: Spectral Adapters for Fine-Grained Video Understanding
by: Ponbagavathi, Thinesh Thiyakesan, et al.
Published: (2026)

Deep Learning-based Point Cloud Registration for Augmented Reality-guided Surgery
by: Weber, Maximilian, et al.
Published: (2024)

CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images
by: Gaggion, Nicolás, et al.
Published: (2023)

Revisiting foundation models for cell instance segmentation
by: Archit, Anwai, et al.
Published: (2026)

Enhancing zero-shot learning in medical imaging: integrating clip with advanced techniques for improved chest x-ray analysis
by: Bhardwaj, Prakhar, et al.
Published: (2025)

GRASPing Anatomy to Improve Pathology Segmentation
by: Li, Keyi, et al.
Published: (2025)

GazeLT: Visual attention-guided long-tailed disease classification in chest radiographs
by: Bhattacharya, Moinak, et al.
Published: (2025)

Detection of subclinical atherosclerosis by image-based deep learning on chest x-ray
by: Gallone, Guglielmo, et al.
Published: (2024)

From Static to Interactive: Adapting Visual in-Context Learners for User-Driven Tasks
by: Schmidt, Carlos, et al.
Published: (2026)

Conquering the Retina: Bringing Visual in-Context Learning to OCT
by: Negrini, Alessio, et al.
Published: (2025)

Bridging spatial awareness and global context in medical image segmentation
by: Alzu'bi, Dalia, et al.
Published: (2025)

A hybrid Kolmogorov-Arnold network for medical image segmentation
by: Bhattacharyya, Deep, et al.
Published: (2026)

Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography
by: Bombiński, Przemysław, et al.
Published: (2024)

Cyto R-CNN and CytoNuke Dataset: Towards reliable whole-cell segmentation in bright-field histological images
by: Raufeisen, Johannes, et al.
Published: (2024)

A data- and compute-efficient chest X-ray foundation model beyond aggressive scaling
by: Wang, Chong, et al.
Published: (2026)

SurgiSAM2: Fine-tuning a foundational model for surgical video anatomy segmentation and detection
by: Kamtam, Devanish N., et al.
Published: (2025)

The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT $\unicode{x2013}$ Multitracer Multicenter Generalization
by: Dexl, Jakob, et al.
Published: (2026)

Efficient Complex-Valued Vision Transformers for MRI Classification Directly from k-Space
by: Rempe, Moritz, et al.
Published: (2026)

Probing Intrinsic Medical Task Relationships: A Contrastive Learning Perspective
by: Muth, Jonas, et al.
Published: (2026)

Action-guided generation of 3D functionality segmentation data
by: Corsetti, Jaime, et al.
Published: (2025)

Epanechnikov nonparametric kernel density estimation based feature-learning in respiratory disease chest X-ray images
by: Marsico, Veronica, et al.
Published: (2025)

In search of truth: Evaluating concordance of AI-based anatomy segmentation models
by: Giebeler, Lena, et al.
Published: (2025)

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge
by: Holste, Gregory, et al.
Published: (2023)

Vascular anatomy-aware self-supervised pre-training for X-ray angiogram analysis
by: Huang, De-Xing, et al.
Published: (2026)