Medical Image Analysis

Papers
(The H4-Index of Medical Image Analysis is 78. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-10-01 to 2024-10-01.)
ArticleCitations
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning723
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis426
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis384
CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation381
Deep neural network models for computational histopathology: A survey378
Recent advances and clinical applications of deep learning in medical image analysis363
The Liver Tumor Segmentation Benchmark (LiTS)322
A survey on active learning and human-in-the-loop deep learning for medical image analysis312
Loss odyssey in medical image segmentation312
PadChest: A large chest x-ray image dataset with multi-label annotated reports309
Transformers in medical imaging: A survey305
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge289
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis283
Accurate brain age prediction with lightweight deep neural networks280
Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks252
Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results248
FAT-Net: Feature adaptive transformers for automated skin lesion segmentation247
Deep learning for chest X-ray analysis: A survey236
TransMorph: Transformer for unsupervised medical image registration225
Applications of deep learning in fundus images: A review214
CS2-Net: Deep learning segmentation of curvilinear structures in m194
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging193
Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study188
Transformer-based unsupervised contrastive learning for histopathological image classification185
Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images177
Models Genesis175
Segment anything model for medical image analysis: An experimental study166
Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation162
Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan162
A survey on incorporating domain knowledge into deep learning for medical image analysis161
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking159
SCS-Net: A Scale and Context Sensitive Network for Retinal Vessel Segmentation151
Surgical data science – from concepts toward clinical translation149
Boundary loss for highly unbalanced segmentation144
Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency140
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images140
Score-based diffusion models for accelerated MRI139
Dual-branch combination network (DCN): Towards accurate diagnosis and lesion segmentation of COVID-19 using CT images139
CycleMorph: Cycle consistent unsupervised deformable image registration137
Diffusion models in medical imaging: A comprehensive survey130
Head and neck tumor segmentation in PET/CT: The HECKTOR challenge129
Supervised learning with cyclegan for low-dose FDG PET image denoising120
Federated learning for computational pathology on gigapixel whole slide images119
AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia115
EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos114
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization114
Global guidance network for breast lesion segmentation in ultrasound images113
ResGANet: Residual group attention network for medical image classification and segmentation112
SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining111
Deep reinforcement learning in medical imaging: A literature review109
HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images107
The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study102
Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning101
Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer100
A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification99
Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review99
Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides99
Test-time adaptable neural networks for robust medical image segmentation99
Ms RED: A novel multi-scale residual encoding and decoding network for skin lesion segmentation99
Boundary-aware context neural network for medical image segmentation97
BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset97
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives96
COVID-AL: The diagnosis of COVID-19 with deep active learning96
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs94
Analysis of the ISIC image datasets: Usage, benchmarks and recommendations93
Triple U-net: Hematoxylin-aware nuclei segmentation with progressive dense feature aggregation90
Triple attention learning for classification of 14 thoracic diseases using chest radiography89
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology88
End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction87
RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval87
TSegNet: An efficient and accurate tooth segmentation network on 3D dental model86
mustGAN: multi-stream Generative Adversarial Networks for MR Image Synthesis86
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy84
Unsupervised brain imaging 3D anomaly detection and segmentation with transformers83
MSCS-DeepLN: Evaluating lung nodule malignancy using multi-scale cost-sensitive neural networks81
Fast and Low-GPU-memory abdomen CT organ segmentation: The FLARE challenge80
Mutual consistency learning for semi-supervised medical image segmentation80
Yottixel – An Image Search Engine for Large Archives of Histopathology Whole Slide Images78
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