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Top Papers: Medizinische Bildsegmentierung (2024)

Die 50 meistzitierten Arbeiten zu Medizinische Bildsegmentierung aus dem Jahr 2024 (von 4.983 insgesamt).

Die automatische Bildsegmentierung ist eine Schlüsseltechnologie für die KI-gestützte Medizin. Algorithmen erkennen und markieren gezielt Organe, Tumore oder Gewebeveränderungen in CT-, MRT- und Ultraschallbildern. Das beschleunigt klinische Workflows und verbessert die Reproduzierbarkeit von Diagnosen. Diese Seite sammelt die wichtigsten Arbeiten aus diesem spezialisierten Forschungsfeld.

#PaperZitationen
1

YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

Chien-Yao Wang, I-Hau Yeh, Hong-Yuan Mark Liao

Lecture notes in computer science

3.286
2

Segment anything in medical images

Jun Ma, Yuting He, Feifei Li et al.

Nature Communications

2.247
3

SegMamba: Long-Range Sequential Modeling Mamba for 3D Medical Image Segmentation

Zhaohu Xing, Tian Ye, Yijun Yang et al.

Lecture notes in computer science

412
4

EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation

Md Mostafijur Rahman, Mustafa Munir, Radu Marculescu

358
5

UNETR++: Delving Into Efficient and Accurate 3D Medical Image Segmentation

Abdelrahman Shaker, Muhammad Maaz, Hanoona Rasheed et al.

IEEE Transactions on Medical Imaging

340
6

Channel prior convolutional attention for medical image segmentation

Hejun Huang, Zuguo Chen, Ying Zou et al.

Computers in Biology and Medicine

282
7

nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation

Fabian Isensee, Tassilo Wald, Constantin Ulrich et al.

Lecture notes in computer science

262
8

U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Jun Ma, Li Fei-Fei, Bo Wang

arXiv (Cornell University)

215
9

Advances in Medical Image Segmentation: A Comprehensive Review of Traditional, Deep Learning and Hybrid Approaches

Yan Xu, Rixiang Quan, Weiting Xu et al.

Bioengineering

209
10

VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Jiacheng Ruan, Suncheng Xiang, Xiang, Suncheng

arXiv (Cornell University)

209
11

Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications

Yuwen Xiong, Zhiqi Li, Yuntao Chen et al.

207
12

Image Data Augmentation Approaches: A Comprehensive Survey and Future Directions

Teerath Kumar, Rob Brennan, Alessandra Mileo et al.

IEEE Access

207
13

Omni-Kernel Network for Image Restoration

Yuning Cui, Wenqi Ren, Alois Knoll

Proceedings of the AAAI Conference on Artificial Intelligence

206
14

Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation

Reza Azad, Leon Niggemeier, Michael Hüttemann et al.

205
15

Deep semi-supervised learning for medical image segmentation: A review

Kai Han, Victor S. Sheng, Yuqing Song et al.

Expert Systems with Applications

198
16

MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation

Cheng Chen, Juzheng Miao, Dufan Wu et al.

Medical Image Analysis

174
17

Brain tumor segmentation in MRI with multi-modality spatial information enhancement and boundary shape correction

Zhiqin Zhu, Ziyu Wang, Guanqiu Qi et al.

Pattern Recognition

168
18

Sparse Dynamic Volume TransUNet with multi-level edge fusion for brain tumor segmentation

Zhiqin Zhu, Mengwei Sun, Guanqiu Qi et al.

Computers in Biology and Medicine

165
19

Equivariant Multi-Modality Image Fusion

Zixiang Zhao, Haowen Bai, Jiangshe Zhang et al.

157
20

Automated Brain Tumor Segmentation and Classification in MRI Using YOLO-Based Deep Learning

Maram Fahaad Almufareh, Muhammad Imran, Abdullah Khan et al.

IEEE Access

155
21

Rethinking FID: Towards a Better Evaluation Metric for Image Generation

Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit et al.

155
22

AnyDoor: Zero-shot Object-level Image Customization

Xi Chen, Lianghua Huang, Liu Yu et al.

144
23

A novel CNN architecture for accurate early detection and classification of Alzheimer’s disease using MRI data

A. M. El-Assy, Hanan M. Amer, Hegazi Ibrahim et al.

Scientific Reports

144
24

VM-UNET-V2: Rethinking Vision Mamba UNet for Medical Image Segmentation

Mingya Zhang, Yue Yu, Jin Sun et al.

Lecture notes in computer science

138
25

CMUNEXT: An Efficient Medical Image Segmentation Network Based on Large Kernel and Skip Fusion

Fenghe Tang, Jianrui Ding, Quan Quan et al.

124
26

Data-efficient Fine-tuning for LLM-based Recommendation

Xinyu Lin, Wenjie Wang, Yongqi Li et al.

121
27

I<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si18.svg" display="inline" id="d1e3125"><mml:msup><mml:mrow/><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:math>U-Net: A dual-path U-Net with rich information interaction for medical image segmentation

Duwei Dai, Caixia Dong, Qingsen Yan et al.

Medical Image Analysis

118
28

A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond

Junyu Chen, Yihao Liu, Shuwen Wei et al.

Medical Image Analysis

115
29

Dual-3DM<sup>3</sup>AD: Mixed Transformer Based Semantic Segmentation and Triplet Pre-Processing for Early Multi-Class Alzheimer’s Diagnosis

Arfat Ahmad Khan, Rakesh Kumar Mahendran, Kumar Perumal et al.

IEEE Transactions on Neural Systems and Rehabilitation Engineering

111
30

Recursive Deformable Pyramid Network for Unsupervised Medical Image Registration

Haiqiao Wang, Dong Ni, Yi Wang

IEEE Transactions on Medical Imaging

103
31

G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation

Md Mostafijur Rahman, Radu Mărculescu

102
32

MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images

Andres Diaz‐Pinto, Sachidanand Alle, Vishwesh Nath et al.

Medical Image Analysis

97
33

SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation

Shehan Perera, Pouyan Navard, Alper Yılmaz

96
34

LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation

Jinhong Wang, Jintai Chen, Danny Z. Chen et al.

Lecture notes in computer science

90
35

Digital Image Processing

Sunil Narumalani, Paul Merani

87
36

Semi-Mamba-UNet: Pixel-level contrastive and cross-supervised visual Mamba-based UNet for semi-supervised medical image segmentation

Chao Ma, Ziyang Wang

Knowledge-Based Systems

83
37

Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation

Ziyang Wang, Jian-Qing Zheng, Yichi Zhang et al.

arXiv (Cornell University)

82
38

Boundary-enhanced dual-stream network for semantic segmentation of high-resolution remote sensing images

Xinghua Li, Linglin Xie, Cai‐Feng Wang et al.

GIScience & Remote Sensing

80
39

SurgicalSAM: Efficient Class Promptable Surgical Instrument Segmentation

Wenxi Yue, Jing Zhang, Kun Hu et al.

Proceedings of the AAAI Conference on Artificial Intelligence

77
40

TUMTraf V2X Cooperative Perception Dataset

Walter Zimmer, Gerhard Arya Wardana, Suren Sritharan et al.

77
41

MAGRes-UNet: Improved Medical Image Segmentation Through a Deep Learning Paradigm of Multi-Attention Gated Residual U-Net

Tahir Hussain, Hayaru Shouno

IEEE Access

76
42

3DUV-NetR+: A 3D hybrid semantic architecture using transformers for brain tumor segmentation with MultiModal MR images

Ilyasse Aboussaleh, Jamal Riffi, Khalid El Fazazy et al.

Results in Engineering

76
43

A Comprehensive Survey of Multi-Level Thresholding Segmentation Methods for Image Processing

Mohammad Amiriebrahimabadi, Zhina Rouhi, Najme Mansouri

Archives of Computational Methods in Engineering

75
44

ESKNet: An enhanced adaptive selection kernel convolution for ultrasound breast tumors segmentation

Gongping Chen, Lu Zhou, Jianxun Zhang et al.

Expert Systems with Applications

75
45

Modality-Agnostic Domain Generalizable Medical Image Segmentation by Multi-Frequency in Multi-Scale Attention

Ju-Hyeon Nam, Nur Suriza Syazwany, Su Jung Kim et al.

74
46

USFM: A universal ultrasound foundation model generalized to tasks and organs towards label efficient image analysis

Jing Jiao, Jin Zhou, Xiaokang Li et al.

Medical Image Analysis

73
47

Adaptive Bidirectional Displacement for Semi-Supervised Medical Image Segmentation

Hanyang Chi, Jian Pang, Bingfeng Zhang et al.

71
48

FATFusion: A functional–anatomical transformer for medical image fusion

Wei Tang, Fazhi He

Information Processing & Management

69
49

Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels

Chenyu You, Weicheng Dai, Fenglin Liu et al.

IEEE Transactions on Pattern Analysis and Machine Intelligence

68
50

Selective and multi-scale fusion Mamba for medical image segmentation

Guangju Li, Qinghua Huang, Wei Wang et al.

Expert Systems with Applications

68

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