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Top Papers: Medizinische Bildsegmentierung (2023)

Die 50 meistzitierten Arbeiten zu Medizinische Bildsegmentierung aus dem Jahr 2023 (von 3.616 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

Segment anything model for medical image analysis: An experimental study

Maciej A. Mazurowski, Haoyu Dong, Hanxue Gu et al.

Medical Image Analysis

629
2

Techniques and Challenges of Image Segmentation: A Review

Ying Yu, Chunping Wang, Qiang Fu et al.

Electronics

309
3

Medical Image Segmentation via Cascaded Attention Decoding

Md. Mostafijur Rahman, Radu Mărculescu

2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

309
4

Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers

Bo Dong, Wenhai Wang, Deng-Ping Fan et al.

CAAI Artificial Intelligence Research

295
5

HiFuse: Hierarchical multi-scale feature fusion network for medical image classification

Xiangzuo Huo, Gang Sun, Shengwei Tian et al.

Biomedical Signal Processing and Control

287
6

DiffIR: Efficient Diffusion Model for Image Restoration

Bin Xia, Yulun Zhang, Shiyin Wang et al.

271
7

Learning with limited annotations: A survey on deep semi-supervised learning for medical image segmentation

Rushi Jiao, Yichi Zhang, Le Ding et al.

Computers in Biology and Medicine

269
8

Deep Learning Attention Mechanism in Medical Image Analysis: Basics and Beyonds

Xiang Li, Minglei Li, Pengfei Yan et al.

International Journal of Network Dynamics and Intelligence

239
9

MPDIoU: A Loss for Efficient and Accurate Bounding Box Regression

Siliang Ma, Yong Xu

arXiv (Cornell University)

216
10

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

Alessa Hering

University of Birmingham Research Portal (University of Birmingham)

207
11

Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets

Benjamin Billot, Colin Magdamo, You Cheng et al.

Proceedings of the National Academy of Sciences

190
12

Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

Shanliang Yao, Runwei Guan, Xiaoyu Huang et al.

IEEE Transactions on Intelligent Vehicles

175
13

Dual Cross-Attention for medical image segmentation

Gorkem Can Ates, Prasoon P. Mohan, Emrah Çelik

Engineering Applications of Artificial Intelligence

172
14

Deep learning based synthesis of MRI, CT and PET: Review and analysis

Sanuwani Dayarathna, Kh Tohidul Islam, Sergio Uribe et al.

Medical Image Analysis

170
15

BBDM: Image-to-Image Translation with Brownian Bridge Diffusion Models

Bo Li, Kaitao Xue, Bin Liu et al.

168
16

SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry

Juan Eugenio Iglesias, Benjamin Billot, Yaël Balbastre et al.

Science Advances

165
17

Base and Meta: A New Perspective on Few-Shot Segmentation

Chunbo Lang, Gong Cheng, Binfei Tu et al.

IEEE Transactions on Pattern Analysis and Machine Intelligence

160
18

MCF: Mutual Correction Framework for Semi-Supervised Medical Image Segmentation

Yongchao Wang, Bin Xiao, Xiuli Bi et al.

157
19

TransMatch: A Transformer-Based Multilevel Dual-Stream Feature Matching Network for Unsupervised Deformable Image Registration

Zeyuan Chen, Yuanjie Zheng, James C. Gee

IEEE Transactions on Medical Imaging

154
20

Using DUCK-Net for polyp image segmentation

Razvan-Gabriel Dumitru, Darius Petelează, Catalin Craciun

Scientific Reports

154
21

Weakly supervised machine learning

Zeyu Ren, Shuihua Wang‎, Yudong Zhang

CAAI Transactions on Intelligence Technology

145
22

Dense extreme inception network for edge detection

Xavier Soria Poma, Ángel D. Sappa, Patricio Humanante et al.

Pattern Recognition

142
23

Robotic ultrasound imaging: State-of-the-art and future perspectives

Zhongliang Jiang, Septimiu E. Salcudean, Nassir Navab

Medical Image Analysis

138
24

PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning

Xiangyang Zhu, Renrui Zhang, Bowei He et al.

134
25

Brain Tumor Classification Using Meta-Heuristic Optimized Convolutional Neural Networks

Sarah Zuhair Kurdi, Mohammed Hasan Ali, Mustafa Musa Jaber et al.

Journal of Personalized Medicine

128
26

Accurate Detection of Alzheimer’s Disease Using Lightweight Deep Learning Model on MRI Data

Ahmed A. Abd El‐Latif, Samia Allaoua Chelloug, Maali Alabdulhafith et al.

Diagnostics

119
27

Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical Segmentation

Peilun Shi, Jianing Qiu, Sai Mu Dalike Abaxi et al.

Diagnostics

117
28

Solving 3D Inverse Problems Using Pre-Trained 2D Diffusion Models

Hyungjin Chung, Dohoon Ryu, Michael T. McCann et al.

114
29

Automated Segmentation of Brain Tumor MRI Images Using Deep Learning

Surendran Rajendran, Suresh Kumar R, Tamilvizhi Thanarajan et al.

IEEE Access

110
30

Eres-UNet++: Liver CT image segmentation based on high-efficiency channel attention and Res-UNet++

Jian Li, Kongyu Liu, Yating Hu et al.

Computers in Biology and Medicine

110
31

Wavelet Diffusion Models are fast and scalable Image Generators

Hao Phung, Quan Dao, Anh Tran

106
32

Natural scene reconstruction from fMRI signals using generative latent diffusion

Furkan Özçelik, Rufin VanRullen

Scientific Reports

104
33

SimpleClick: Interactive Image Segmentation with Simple Vision Transformers

Qin Liu, Zhenlin Xu, Gedas Bertasius et al.

101
34

Directional Connectivity-based Segmentation of Medical Images

Ziyun Yang, Sina Farsiu

101
35

Image semantic segmentation approach based on DeepLabV3 plus network with an attention mechanism

Yanyan Liu, Xiaotian Bai, Jiafei Wang et al.

Engineering Applications of Artificial Intelligence

101
36

Recent Advancements and Future Prospects in Active Deep Learning for Medical Image Segmentation and Classification

Tariq Mahmood, Amjad Rehman, Tanzila Saba et al.

IEEE Access

101
37

BiSeNet V3: Bilateral segmentation network with coordinate attention for real-time semantic segmentation

Tsung‐Han Tsai, Yu-Wei Tseng

Neurocomputing

99
38

ST-Unet: Swin Transformer boosted U-Net with Cross-Layer Feature Enhancement for medical image segmentation

Jing Zhang, Qiuge Qin, Qi Ye et al.

Computers in Biology and Medicine

98
39

3D Medical image segmentation using parallel transformers

Qingsen Yan, Shengqiang Liu, Songhua Xu et al.

Pattern Recognition

98
40

Semantics lead all: Towards unified image registration and fusion from a semantic perspective

Housheng Xie, Yukuan Zhang, Junhui Qiu et al.

Information Fusion

97
41

Image thresholding approaches for medical image segmentation - short literature review

Sandra Jardim, João António, Carlos León de Mora

Procedia Computer Science

97
42

Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation

Arman Avesta, Sajid Hossain, MingDe Lin et al.

Bioengineering

96
43

Masked Image Modeling Advances 3D Medical Image Analysis

Zekai Chen, Devansh Agarwal, K.K. Aggarwal et al.

2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

92
44

Swin Unet3D: a three-dimensional medical image segmentation network combining vision transformer and convolution

Yimin Cai, Yuqing Long, Zhenggong Han et al.

BMC Medical Informatics and Decision Making

91
45

Interpretable Multi-Modal Image Registration Network Based on Disentangled Convolutional Sparse Coding

Xin Deng, Enpeng Liu, Shengxi Li et al.

IEEE Transactions on Image Processing

89
46

Diverse Sample Generation: Pushing the Limit of Generative Data-Free Quantization

Haotong Qin, Yifu Ding, Xiangguo Zhang et al.

IEEE Transactions on Pattern Analysis and Machine Intelligence

89
47

Flexible Fusion Network for Multi-Modal Brain Tumor Segmentation

Hengyi Yang, Tao Zhou, Yi Zhou et al.

IEEE Journal of Biomedical and Health Informatics

89
48

Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation

Zhiqiang Shen, Peng Cao, Hua Yang et al.

88
49

Implicit Neural Representation in Medical Imaging: A Comparative Survey

Amirali Molaei, Amirhossein Aminimehr, Armin Tavakoli et al.

88
50

XNet: Wavelet-Based Low and High Frequency Fusion Networks for Fully- and Semi-Supervised Semantic Segmentation of Biomedical Images

Yanfeng Zhou, Jiaxing Huang, Chenlong Wang et al.

87

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