Cover Image

Shortcut Learning in Medical Image Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Lin, Manxi, Weng, Nina, Mikolaj, Kamil, Bashir, Zahra, Svendsen, Morten Bo Søndergaard, Tolsgaard, Martin, Christensen, Anders Nymark, Feragen, Aasa
Format:	Preprint
Published:	2024
Subjects:	Image and Video Processing Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment
by: Pegios, Paraskevas, et al.
Published: (2024)

Testing of Deep Learning Model in Real World Clinical Setting: A Case Study in Obstetric Ultrasound
by: Wong, Chun Kit, et al.
Published: (2024)

Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models
by: Olsen, Markus Ditlev Sjøgren, et al.
Published: (2024)

Explainable fetal ultrasound quality assessment with progressive concept bottleneck models
by: Lin, Manxi, et al.
Published: (2022)

Weight Space Correlation Analysis: Quantifying Feature Utilization in Deep Learning Models
by: Wong, Chun Kit, et al.
Published: (2025)

A Framework for Exploring and Disentangling Intersectional Bias: A Case Study in Fetal Ultrasound
by: Elgebaly, Aya, et al.
Published: (2026)

Investigating Label Bias and Representational Sources of Age-Related Disparities in Medical Segmentation
by: Parikh, Aditya, et al.
Published: (2025)

Are demographically invariant models and representations in medical imaging fair?
by: Petersen, Eike, et al.
Published: (2023)

Learning semantic image quality for fetal ultrasound from noisy ranking annotation
by: Lin, Manxi, et al.
Published: (2024)

MozzaVID: Mozzarella Volumetric Image Dataset
by: Pieta, Pawel Tomasz, et al.
Published: (2024)

General Methods Make Great Domain-specific Foundation Models: A Case-study on Fetal Ultrasound
by: Ambsdorf, Jakob, et al.
Published: (2025)

Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation
by: Zhou, Yinchi, et al.
Published: (2024)

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

MDN: Mamba-Driven Dualstream Network For Medical Hyperspectral Image Segmentation
by: Lin, Shijie, et al.
Published: (2025)

Invited Paper: BitMedViT: Ternary-Quantized Vision Transformer for Medical AI Assistants on the Edge
by: Walczak, Mikolaj, et al.
Published: (2025)

Multi-modal data generation with a deep metric variational autoencoder
by: Sundgaard, Josefine Vilsbøll, et al.
Published: (2022)

3D Skin Segmentation Methods in Medical Imaging: A Comparison
by: Paccini, Martina, et al.
Published: (2025)

Improving Lesion Segmentation in Medical Images by Global and Regional Feature Compensation
by: Wang, Chuhan, et al.
Published: (2025)

Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation
by: Liu, Houze, et al.
Published: (2024)

CATFA-Net: A Trans-Convolutional Approach for Accurate Medical Image Segmentation
by: Mallick, Siddhartha, et al.
Published: (2026)

Using Diffusion Models to Generate Synthetic Labelled Data for Medical Image Segmentation
by: Saragih, Daniel, et al.
Published: (2023)

Pixels Under Pressure: Exploring Fine-Tuning Paradigms for Foundation Models in High-Resolution Medical Imaging
by: TehraniNasab, Zahra, et al.
Published: (2025)

UNet-3D with Adaptive TverskyCE Loss for Pancreas Medical Image Segmentation
by: Zhang, Xubei, et al.
Published: (2025)

Domain Influence in MRI Medical Image Segmentation: spatial versus k-space inputs
by: Gösche, Erik, et al.
Published: (2024)

SplitFed-CL: A Split Federated Co-Learning Framework for Medical Image Segmentation with Inaccurate Labels
by: Kafshgari, Zahra Hafezi, et al.
Published: (2026)

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

Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation
by: Sheng, Jiaxi, et al.
Published: (2025)

Optimizing Prompt Strategies for SAM: Advancing lesion Segmentation Across Diverse Medical Imaging Modalities
by: Wang, Yuli, et al.
Published: (2024)

USEANet: Ultrasound-Specific Edge-Aware Multi-Branch Network for Lightweight Medical Image Segmentation
by: Gao, Jingyi, et al.
Published: (2025)

Human Gaze-based Dual Teacher Guidance Learning for Semi-Supervised Medical Image Segmentation
by: Ge, Rongjun, et al.
Published: (2026)

Skill-Evolving Grounded Reasoning for Free-Text Promptable 3D Medical Image Segmentation
by: Zhang, Tongrui, et al.
Published: (2026)

Segment Anything in Medical Images and Videos: Benchmark and Deployment
by: Ma, Jun, et al.
Published: (2024)

MedSegNet10: A Publicly Accessible Network Repository for Split Federated Medical Image Segmentation
by: Shiranthika, Chamani, et al.
Published: (2025)

M$^4$oE: A Foundation Model for Medical Multimodal Image Segmentation with Mixture of Experts
by: Jiang, Yufeng, et al.
Published: (2024)

Bigger Isn't Always Better: Towards a General Prior for Medical Image Reconstruction
by: Glaszner, Lukas, et al.
Published: (2025)

Advancing Medical Image Segmentation via Self-supervised Instance-adaptive Prototype Learning
by: Liang, Guoyan, et al.
Published: (2025)

FEFormer: Frequency-enhanced Vision Transformer for Generic Knowledge Extraction and Adaptive Feature Fusion in Volumetric Medical Image Segmentation
by: Yang, Jin, et al.
Published: (2026)

Synthetic Volumetric Data Generation Enables Zero-Shot Generalization of Foundation Models in 3D Medical Image Segmentation
by: Chakrabarty, Satrajit, et al.
Published: (2026)

TransLK-Net: Entangling Transformer and Large Kernel for Progressive and Collaborative Feature Encoding and Decoding in Medical Image Segmentation
by: Yang, Jin, et al.
Published: (2025)

Dante: An Open Source Model Pre-Training and Fine-Tuning Tool for the Dafne Federated Framework for Medical Image Segmentation
by: Timpano, Giuseppe, et al.
Published: (2026)