Cover Image

Benchmarking CNN-based Models against Transformer-based Models for Abdominal Multi-Organ Segmentation on the RATIC Dataset

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bayer, Lukas, Bhat, Sheethal, Maier, Andreas
Format:	Preprint
Published:	2026
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

The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset
by: Rudie, Jeffrey D., et al.
Published: (2024)

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)

CXR-CML: Improved zero-shot classification of long-tailed multi-label diseases in Chest X-Rays
by: Madhipati, Rajesh, et al.
Published: (2025)

Addressing Data Scarcity in 3D Trauma Detection through Self-Supervised and Semi-Supervised Learning with Vertex Relative Position Encoding
by: Chaudhary, Shivam, et al.
Published: (2026)

Review of Zero-Shot and Few-Shot AI Algorithms in The Medical Domain
by: Badawi, Maged, et al.
Published: (2024)

ProtoCLIP: Prototype-Aligned Latent Refinement for Robust Zero-Shot Chest X-Ray Classification
by: Kittler, Florian, et al.
Published: (2026)

Retina-RAG: Retrieval-Augmented Vision-Language Modeling for Joint Retinal Diagnosis and Clinical Report Generation
by: Zaian, Abdelrahman, et al.
Published: (2026)

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

Attention-Guided Erasing: A Novel Augmentation Method for Enhancing Downstream Breast Density Classification
by: Panambur, Adarsh Bhandary, et al.
Published: (2024)

Benchmarking Multi-Organ Segmentation Tools for Multi-Parametric T1-weighted Abdominal MRI
by: Tran, Nicole, et al.
Published: (2025)

Cut to the Mix: Simple Data Augmentation Outperforms Elaborate Ones in Limited Organ Segmentation Datasets
by: Liu, Chang, et al.
Published: (2026)

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

LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation
by: Bhuiyan, Mohammad Robaitul Islam, et al.
Published: (2026)

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

Exemplar Med-DETR: Toward Generalized and Robust Lesion Detection in Mammogram Images and beyond
by: Bhat, Sheethal, et al.
Published: (2025)

Benchmarking CNN- and Transformer-Based Models for Surgical Instrument Segmentation in Robotic-Assisted Surgery
by: Ameli, Sara
Published: (2026)

Deep Mutual Learning among Partially Labeled Datasets for Multi-Organ Segmentation
by: Liu, Xiaoyu, et al.
Published: (2024)

AMD-HookNet++: Evolution of AMD-HookNet with Hybrid CNN-Transformer Feature Enhancement for Glacier Calving Front Segmentation
by: Wu, Fei, et al.
Published: (2025)

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

Hybrid(Transformer+CNN)-based Polyp Segmentation
by: Baduwal, Madan
Published: (2025)

A survey of the Vision Transformers and their CNN-Transformer based Variants
by: Khan, Asifullah, et al.
Published: (2023)

Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation
by: Čevora, Kate, et al.
Published: (2024)

Coarse-to-Fine Non-rigid Multi-modal Image Registration for Historical Panel Paintings based on Crack Structures
by: Sindel, Aline, et al.
Published: (2026)

Channel Boosted CNN-Transformer-based Multi-Level and Multi-Scale Nuclei Segmentation
by: Rauf, Zunaira, et al.
Published: (2024)

Scribbles for All: Benchmarking Scribble Supervised Segmentation Across Datasets
by: Boettcher, Wolfgang, et al.
Published: (2024)

CNN-based Multi-In-Multi-Out Model for Efficient Spatiotemporal Prediction
by: Jin, Hyeonseok
Published: (2026)

Fast Multi-Organ Fine Segmentation in CT Images with Hierarchical Sparse Sampling and Residual Transformer
by: Guo, Xueqi, et al.
Published: (2025)

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

OmniPlantSeg: Species Agnostic 3D Point Cloud Organ Segmentation for High-Resolution Plant Phenotyping Across Modalities
by: Gilson, Andreas, et al.
Published: (2025)

A Category-Fragment Segmentation Framework for Pelvic Fracture Segmentation in X-ray Images
by: Liu, Daiqi, et al.
Published: (2025)

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

HBFormer: A Hybrid-Bridge Transformer for Microtumor and Miniature Organ Segmentation
by: Zheng, Fuchen, et al.
Published: (2025)

CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation
by: Wu, Lanhu, 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)

DyABD: The Abdominal Muscle Segmentation in Dynamic MRI Benchmark
by: Belton, Niamh, et al.
Published: (2026)

MVTOP: Multi-View Transformer-based Object Pose-Estimation
by: Ranftl, Lukas, et al.
Published: (2025)

CNN-based Game State Detection for a Foosball Table
by: Hagens, David, et al.
Published: (2024)

Multi-dimension Transformer with Attention-based Filtering for Medical Image Segmentation
by: Wang, Wentao, et al.
Published: (2024)

MUSTER: A Multi-scale Transformer-based Decoder for Semantic Segmentation
by: Xu, Jing, et al.
Published: (2022)

Challenges in Deep Learning-Based Small Organ Segmentation: A Benchmarking Perspective for Medical Research with Limited Datasets
by: Konrad, Phongsakon Mark, et al.
Published: (2025)