Cover Image

Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Čevora, Kate, Glocker, Ben, Bai, Wenjia
Format:	Preprint
Published:	2024
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

MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation
by: Jha, Debesh, et al.
Published: (2024)

Benchmarking of Deep Learning Methods for Generic MRI Multi-Organ Abdominal Segmentation
by: Krishnaswamy, Deepa, et al.
Published: (2025)

A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation
by: Huang, Ziyan, et al.
Published: (2023)

Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging cases
by: Luo, Xiangde, et al.
Published: (2024)

Universal and Extensible Language-Vision Models for Organ Segmentation and Tumor Detection from Abdominal Computed Tomography
by: Liu, Jie, et al.
Published: (2024)

Towards Automatic Abdominal MRI Organ Segmentation: Leveraging Synthesized Data Generated From CT Labels
by: Ciausu, Cosmin, et al.
Published: (2024)

Radio-opaque artefacts in digital mammography: automatic detection and analysis of downstream effects
by: Schueppert, Amelia, et al.
Published: (2024)

Devil is in Details: Locality-Aware 3D Abdominal CT Volume Generation for Self-Supervised Organ Segmentation
by: Wang, Yuran, et al.
Published: (2024)

MRISegmentator-Abdomen: A Fully Automated Multi-Organ and Structure Segmentation Tool for T1-weighted Abdominal MRI
by: Zhuang, Yan, et al.
Published: (2024)

FMD-TransUNet: Abdominal Multi-Organ Segmentation Based on Frequency Domain Multi-Axis Representation Learning and Dual Attention Mechanisms
by: Lu, Fang, et al.
Published: (2025)

Zero-shot 3D Segmentation of Abdominal Organs in CT Scans Using Segment Anything Model 2: Adapting Video Tracking Capabilities for 3D Medical Imaging
by: Yamagishi, Yosuke, et al.
Published: (2024)

Vector Representations of Vessel Trees
by: Batten, James, et al.
Published: (2025)

UNSURF: Uncertainty Quantification for Cortical Surface Reconstruction of Clinical Brain MRIs
by: Mehta, Raghav, et al.
Published: (2025)

Robustness Evaluation of a Foundation Segmentation Model Under Simulated Domain Shifts in Abdominal CT: Implications for Health Digital Twin Deployment
by: Basu, Sanghati
Published: (2026)

On Enhancing Brain Tumor Segmentation Across Diverse Populations with Convolutional Neural Networks
by: Maani, Fadillah, et al.
Published: (2024)

Combining imaging and shape features for prediction tasks of Alzheimer's disease classification and brain age regression
by: Shehata, Nairouz, et al.
Published: (2025)

Unlocking Robust Segmentation Across All Age Groups via Continual Learning
by: Liu, Chih-Ying, et al.
Published: (2024)

CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentation
by: Yu, Yongrui, et al.
Published: (2024)

Cardiovascular disease classification using radiomics and geometric features from cardiac CT
by: Mittal, Ajay, et al.
Published: (2025)

Deep Learning Segmentation of Ascites on Abdominal CT Scans for Automatic Volume Quantification
by: Hou, Benjamin, et al.
Published: (2024)

Dynamic U-Net: Adaptively Calibrate Features for Abdominal Multi-organ Segmentation
by: Yang, Jin, et al.
Published: (2024)

MSWAL: 3D Multi-class Segmentation of Whole Abdominal Lesions Dataset
by: Wu, Zhaodong, et al.
Published: (2025)

Fuzzy Attention-based Border Rendering Network for Lung Organ Segmentation
by: Zhang, Sheng, et al.
Published: (2024)

Uncertainty Driven Bottleneck Attention U-net for Organ at Risk Segmentation
by: Nazib, Abdullah, et al.
Published: (2023)

LSU-Net: Lightweight Automatic Organs Segmentation Network For Medical Images
by: Ding, Yujie, et al.
Published: (2025)

Multi-scale Cascaded Foundation Model for Whole-body Organs-at-risk Segmentation
by: Hao, Rui, et al.
Published: (2024)

Modality-Independent Explainable Detection of Inaccurate Organ Segmentations Using Denoising Autoencoders
by: Lippenszky, Levente, et al.
Published: (2025)

ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation
by: Bao, Muyi, et al.
Published: (2025)

MOSAIC: A Multi-View 2.5D Organ Slice Selector with Cross-Attentional Reasoning for Anatomically-Aware CT Localization in Medical Organ Segmentation
by: Ghouse, Hania, et al.
Published: (2025)

CF-Seg: Counterfactuals meet Segmentation
by: Mehta, Raghav, et al.
Published: (2025)

Prompt2SegCXR:Prompt to Segment All Organs and Diseases in Chest X-rays
by: Zami, Abduz, et al.
Published: (2025)

A Foundation Model for Brain Lesion Segmentation with Mixture of Modality Experts
by: Zhang, Xinru, et al.
Published: (2024)

Cross-Organ and Cross-Scanner Adenocarcinoma Segmentation using Rein to Fine-tune Vision Foundation Models
by: Cai, Pengzhou, et al.
Published: (2024)

MD-RWKV-UNet: Scale-Aware Anatomical Encoding with Cross-Stage Fusion for Multi-Organ Segmentation
by: Fang, Zhuoyi
Published: (2026)

Deep Learning-Based Automated Workflow for Accurate Segmentation and Measurement of Abdominal Organs in CT Scans
by: Shastry, Praveen, et al.
Published: (2025)

SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints
by: Basaran, Berke Doga, et al.
Published: (2024)

Snake with Shifted Window: Learning to Adapt Vessel Pattern for OCTA Segmentation
by: Chen, Xinrun, et al.
Published: (2024)

Segmenting Medical Images: From UNet to Res-UNet and nnUNet
by: Huang, Lina, et al.
Published: (2024)

BAISeg: Boundary Assisted Weakly Supervised Instance Segmentation
by: Wang, Tengbo, et al.
Published: (2024)

Data Quality Matters: Quantifying Image Quality Impact on Machine Learning Performance
by: Steinhauser, Christian, et al.
Published: (2025)