Top Papers: Medizinische Bildsegmentierung (2020)

Die 50 meistzitierten Arbeiten zu Medizinische Bildsegmentierung aus dem Jahr 2020 (von 4.068 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.

2018 2019 2020 2021

#	Paper	Zitationen
1	UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation Huimin Huang, Lanfen Lin, Ruofeng Tong et al. —	2.562
2	Morphological Image Operators Advances in imaging and electron physics	880
3	A survey of loss functions for semantic segmentation Shruti Jadon —	865
4	Deep Learning for Cardiac Image Segmentation: A Review Chen Chen, Chen Qin, Huaqi Qiu et al. Frontiers in Cardiovascular Medicine	807
5	SOLO: Segmenting Objects by Locations Xinlong Wang, Tao Kong, Chunhua Shen et al. Lecture notes in computer science	771
6	Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation Junhao Wen, Elina Thibeau–Sutre, Mauricio Diaz-Melo et al. Medical Image Analysis	717
7	Deep Learning in Medical Image Analysis Heang‐Ping Chan, Ravi K. Samala, Lubomir M. Hadjiiski et al. Advances in experimental medicine and biology	698
8	Deep learning in medical image registration: a review Yabo Fu, Yang Lei, Tonghe Wang et al. Physics in Medicine and Biology	625
9	FastSurfer - A fast and accurate deep learning based neuroimaging pipeline Leonie Henschel, Sailesh Conjeti, Santiago Estrada et al. NeuroImage	605
10	3D Deep Learning on Medical Images: A Review Satya P. Singh MDPI (MDPI AG)	593
11	RPM-Net: Robust Point Matching Using Learned Features Zi Jian Yew, Gim Hee Lee —	557
12	A survey on instance segmentation: state of the art Abdul Mueed Hafiz, Ghulam Mohiuddin Bhat International Journal of Multimedia Information Retrieval	473
13	Star-convex Polyhedra for 3D Object Detection and Segmentation in Microscopy Martin Weigert, Uwe Schmidt, Robert Haase et al. —	468
14	Deep learning approaches to biomedical image segmentation Intisar Rizwan I Haque, Jeremiah Neubert Informatics in Medicine Unlocked	456
15	MA-Net: A Multi-Scale Attention Network for Liver and Tumor Segmentation Tongle Fan, Guanglei Wang, Yan Li et al. IEEE Access	439
16	Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation Yudong Zhang, Zhengchao Dong, Shuihua Wang‎ et al. Information Fusion	438
17	Boundary loss for highly unbalanced segmentation Hoel Kervadec, Jihene Bouchtiba, Christian Desrosiers et al. Medical Image Analysis	425
18	Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation Cheng Chen, Qi Dou, Hao Chen et al. IEEE Transactions on Medical Imaging	414
19	Shape-Aware Semi-supervised 3D Semantic Segmentation for Medical Images Shuailin Li, Chuyu Zhang, Xuming He Lecture notes in computer science	397
20	Evolution of Image Segmentation using Deep Convolutional Neural Network: A Survey Farhana Sultana, Abu Sufian, Paramartha Dutta Knowledge-Based Systems	339
21	Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images Yue Zhou, Houjin Chen, Yanfeng Li et al. Medical Image Analysis	322
22	View-GCN: View-Based Graph Convolutional Network for 3D Shape Analysis Xin Wei, Ruixuan Yu, Jian Sun —	314
23	Early Detection of Alzheimer’s Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning Dan Pan, An Zeng, Longfei Jia et al. Frontiers in Neuroscience	313
24	Attention Gate ResU-Net for Automatic MRI Brain Tumor Segmentation Jianxin Zhang, Zongkang Jiang, Jing Dong et al. IEEE Access	307
25	A review on medical image denoising algorithms Sameera V. Mohd Sagheer, Sudhish N. George Biomedical Signal Processing and Control	300
26	Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network Michał Byra, Piotr Jarosik, Aleksandra Szubert et al. Biomedical Signal Processing and Control	298
27	Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets Marc-André Schulz, B.T. Thomas Yeo, Joshua T Vogelstein et al. Nature Communications	292
28	Image segmentation evaluation: a survey of methods Zhaobin Wang, Enlong Wang, Ying Zhu Artificial Intelligence Review	282
29	Cross-modality deep feature learning for brain tumor segmentation Dingwen Zhang, Guohai Huang, Qiang Zhang et al. Pattern Recognition	270
30	Machine learning techniques for biomedical image segmentation: An overview of technical aspects and introduction to state‐of‐art applications Hyunseok Seo, Masoud Badiei Khuzani, Varun Vasudevan et al. Medical Physics	263
31	Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks Tony C. W. Mok, Albert C. S. Chung Rare & Special e-Zone (The Hong Kong University of Science and Technology)	258
32	Brain tumor classification using a hybrid deep autoencoder with Bayesian fuzzy clustering-based segmentation approach P. M. Siva Raja, Antony Viswasa rani Journal of Applied Biomedicine	248
33	Artificial Intelligence Image Recognition Method Based on Convolutional Neural Network Algorithm Youhui Tian IEEE Access	240
34	Unsupervised Learning of Image Segmentation Based on Differentiable Feature Clustering Wonjik Kim, Asako Kanezaki, Masayuki Tanaka IEEE Transactions on Image Processing	238
35	Resolution Adaptive Networks for Efficient Inference Le Yang, Yizeng Han, Xi Chen et al. —	234
36	Self-supervision with Superpixels: Training Few-Shot Medical Image Segmentation Without Annotation Cheng Ouyang, Carlo Biffi, Chen Chen et al. Lecture notes in computer science	234
37	Distilling Knowledge From Graph Convolutional Networks Yiding Yang, Jiayan Qiu, Mingli Song et al. —	229
38	MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer’s Disease: A Survey Nagaraj Yamanakkanavar, Jae Young Choi, Bumshik Lee Sensors	215
39	DeepSeg: deep neural network framework for automatic brain tumor segmentation using magnetic resonance FLAIR images Ramy A. Zeineldin, Mohamed E. Karar, Jan Coburger et al. International Journal of Computer Assisted Radiology and Surgery	214
40	Variability and reproducibility in deep learning for medical image segmentation Félix Renard, Soulaimane Guedria, Noël De Palma et al. Scientific Reports	212
41	Digital Image Processing 3rd ed Rafael C. González, Roger Woods —	207
42	Segmentation of breast ultrasound image with semantic classification of superpixels Qinghua Huang, Yonghao Huang, Yaozhong Luo et al. Medical Image Analysis	203
43	Segmentation and Feature Extraction in Medical Imaging: A Systematic Review Chiranji Lal Chowdhary, D. P. Acharjya Procedia Computer Science	198
44	An efficient Harris hawks-inspired image segmentation method Erick Rodríguez-Esparza, Laura A. Zanella-Calzada, Diego Oliva et al. Expert Systems with Applications	195
45	Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy Mostefa Ben Naceur, Mohamed Akil, Rachida Saouli et al. Medical Image Analysis	191
46	Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN Heran Yang, Jian Sun, Aaron Carass et al. IEEE Transactions on Medical Imaging	184
47	Liver Tumor Segmentation in CT Scans Using Modified SegNet Sultan Almotairi, Ghada Kareem, Mohamed Aouf et al. Sensors	184
48	Segmentation of the multimodal brain tumor image used the multi-pathway architecture method based on 3D FCN Jindong Sun, Yanjun Peng, Yanfei Guo et al. Neurocomputing	182
49	Diagnosis of Alzheimer's disease using universum support vector machine based recursive feature elimination (USVM-RFE) Bharat Richhariya, M. Tanveer, Ashraf Haroon Rashid Biomedical Signal Processing and Control	179
50	Data-Efficient Image Recognition with Contrastive Predictive Coding Olivier J. Hénaff International Conference on Machine Learning	177

Top Papers: Medizinische Bildsegmentierung (2020)

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