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Top Papers: Medizinische Bildsegmentierung (2021)

Die 50 meistzitierten Arbeiten zu Medizinische Bildsegmentierung aus dem Jahr 2021 (von 3.981 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

U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications

Nahian Siddique, Sidike Paheding, Colin Elkin et al.

IEEE Access

1.835
2

IEEE Transactions on Image Processing

Dirección de Gestión del Conocimiento

Universidad Peruana de Ciencias Aplicadas (UPC)

1.537
3

A review of medical image data augmentation techniques for deep learning applications

Phillip Chlap, Hang Min, Nym Vandenberg et al.

Journal of Medical Imaging and Radiation Oncology

915
4

TransBTS: Multimodal Brain Tumor Segmentation Using Transformer

Wenxuan Wang, Chen Chen, Meng Ding et al.

Lecture notes in computer science

871
5

A Review of Deep-Learning-Based Medical Image Segmentation Methods

Xiangbin Liu, Liping Song, Shuai Liu et al.

Sustainability

835
6

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation

Michael Yeung, Evis Sala, Carola‐Bibiane Schönlieb et al.

Computerized Medical Imaging and Graphics

608
7

Loss odyssey in medical image segmentation

Jun Ma, Jianan Chen, Matthew Ng et al.

Medical Image Analysis

596
8

CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

Yutong Xie, Jianpeng Zhang, Chunhua Shen et al.

Lecture notes in computer science

575
9

A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network

Francisco Javier Díaz Pernas, Mario Martínez‐Zarzuela, Míriam Antón‐Rodríguez et al.

Healthcare

513
10

Brain tumor detection and classification using machine learning: a comprehensive survey

Javaria Amin, Muhammad Sharif, Anandakumar Haldorai et al.

Complex & Intelligent Systems

443
11

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge

Victor M. Campello, Polyxeni Gkontra, Cristian Izquierdo et al.

IEEE Transactions on Medical Imaging

419
12

Statistical Shape Analysis

Mengyu Dai, Sebastian Kurtek, Eric Klassen et al.

418
13

The ANTsX ecosystem for quantitative biological and medical imaging

Nicholas J. Tustison, Philip A. Cook, Andrew J. Holbrook et al.

Scientific Reports

357
14

CycleMorph: Cycle consistent unsupervised deformable image registration

Boah Kim, Dong Hwan Kim, Seong Ho Park et al.

Medical Image Analysis

299
15

Fuzzy System Based Medical Image Processing for Brain Disease Prediction

Mandong Hu, Yi Zhong, Shuxuan Xie et al.

Frontiers in Neuroscience

285
16

A Transfer Learning Approach for Early Diagnosis of Alzheimer’s Disease on MRI Images

Atif Mehmood, Shuyuan Yang, Zhixi Feng et al.

Neuroscience

276
17

Prospective assessment of breast cancer risk from multimodal multiview ultrasound images via clinically applicable deep learning

Xuejun Qian, Jing Pei, Hui Zheng et al.

Nature Biomedical Engineering

241
18

Efficient Semi-supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency

Xiangde Luo, Wenjun Liao, Jieneng Chen et al.

Lecture notes in computer science

233
19

Learned Initializations for Optimizing Coordinate-Based Neural Representations

Matthew Tancik, Ben Mildenhall, Terrance Wang et al.

216
20

Review of multi-view 3D object recognition methods based on deep learning

Shaohua Qi, Xin Ning, Guowei Yang et al.

Displays

216
21

Deep Learning for Brain Tumor Segmentation: A Survey of State-of-the-Art

Tirivangani Magadza, Serestina Viriri

Journal of Imaging

211
22

A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification

Jie Zhang, Bowen Zheng, Ang Gao et al.

Magnetic Resonance Imaging

207
23

Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities

Tongxue Zhou, Stéphane Canu, Pierre Véra et al.

IEEE Transactions on Image Processing

207
24

Deep reinforcement learning in medical imaging: A literature review

S. Kevin Zhou, Ngan Le, Khoa Luu et al.

HAL (Le Centre pour la Communication Scientifique Directe)

198
25

Medical Image Segmentation using Squeeze-and-Expansion Transformers

Shaohua Li, Xiuchao Sui, Xiangde Luo et al.

197
26

Synthetic Vasculature Datsets

Bumgarner, Jacob

Harvard Dataverse

189
27

Brain tumor detection in MR image using superpixels, principal component analysis and template based K-means clustering algorithm

Md Khairul Islam, Md Shahin Ali, Md Sipon Miah et al.

Machine Learning with Applications

178
28

SynthMorph: Learning Contrast-Invariant Registration Without Acquired Images

Malte Hoffmann, Benjamin Billot, Douglas N. Greve et al.

IEEE Transactions on Medical Imaging

175
29

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

Zhewei Yao, Amir Gholami, Sheng Shen et al.

Proceedings of the AAAI Conference on Artificial Intelligence

175
30

A FIJI macro for quantifying pattern in extracellular matrix

Esther Wershof, Danielle Park, David J. Barry et al.

Life Science Alliance

162
31

SAR-U-Net: Squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography

Jinke Wang, Peiqing Lv, Haiying Wang et al.

Computer Methods and Programs in Biomedicine

161
32

A Novel Deep Learning Method for Recognition and Classification of Brain Tumors from MRI Images

Momina Masood, Tahira Nazir, Marriam Nawaz et al.

Diagnostics

158
33

MSU-Net: Multi-Scale U-Net for 2D Medical Image Segmentation

Run Su, Deyun Zhang, Jinhuai Liu et al.

Frontiers in Genetics

157
34

Alzheimer's disease detection using depthwise separable convolutional neural networks

Junxiu Liu, Mingxing Li, Yuling Luo et al.

Computer Methods and Programs in Biomedicine

155
35

An Effective Multimodal Image Fusion Method Using MRI and PET for Alzheimer's Disease Diagnosis

Juan Song, Jian Zheng, Ping Li et al.

Frontiers in Digital Health

154
36

Deep learning based pipelines for Alzheimer's disease diagnosis: A comparative study and a novel deep-ensemble method

Andrea Loddo, Sara Buttau, Cecilia Di Ruberto

Computers in Biology and Medicine

152
37

On the usage of average Hausdorff distance for segmentation performance assessment: hidden error when used for ranking

Orhun Utku Aydin, Abdel Aziz Taha, Adam Hilbert et al.

European Radiology Experimental

149
38

A Novel Evolutionary Arithmetic Optimization Algorithm for Multilevel Thresholding Segmentation of COVID-19 CT Images

Laith Abualigah, Ali Diabat, Putra Sumari et al.

Processes

149
39

RFNet: Region-aware Fusion Network for Incomplete Multi-modal Brain Tumor Segmentation

Yuhang Ding, Xin Yu, Yi Yang

2021 IEEE/CVF International Conference on Computer Vision (ICCV)

146
40

Discrimination-aware Network Pruning for Deep Model Compression

Jing Liu, Bohan Zhuang, Zhuangwei Zhuang et al.

IEEE Transactions on Pattern Analysis and Machine Intelligence

142
41

3D Multi-Attention Guided Multi-Task Learning Network for Automatic Gastric Tumor Segmentation and Lymph Node Classification

Yongtao Zhang, Haimei Li, Jie Du et al.

IEEE Transactions on Medical Imaging

142
42

ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration

Junyu Chen, Yufan He, Eric C. Frey et al.

arXiv (Cornell University)

139
43

Hybrid dilation and attention residual U-Net for medical image segmentation

Zekun Wang, Yanni Zou, Peter Liu

Computers in Biology and Medicine

137
44

ERV-Net: An efficient 3D residual neural network for brain tumor segmentation

Xinyu Zhou, Xuanya Li, Kai Hu et al.

Expert Systems with Applications

134
45

Masked-attention Mask Transformer for Universal Image Segmentation

Bowen Cheng, Ishan Misra, Alexander G. Schwing et al.

arXiv (Cornell University)

128
46

MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning

Xiangde Luo, Guotai Wang, Tao Song et al.

Medical Image Analysis

125
47

Brain tumor prediction on MR images with semantic segmentation by using deep learning network and 3D imaging of tumor region

Gökay Karayeğen, Mehmet Feyzi Akşahin

Biomedical Signal Processing and Control

123
48

TransBTS: Multimodal Brain Tumor Segmentation Using Transformer

Wenxuan Wang, Chen Chen, Meng Ding et al.

arXiv (Cornell University)

123
49

Marginal loss and exclusion loss for partially supervised multi-organ segmentation

Gonglei Shi, Li Xiao, Yang Chen et al.

Medical Image Analysis

122
50

Improved U-Net architecture with VGG-16 for brain tumor segmentation

Sourodip Ghosh, Aunkit Chaki, KC Santosh

Physical and Engineering Sciences in Medicine

122

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