Medical Image Analysis

Papers
(The H4-Index of Medical Image Analysis is 71. 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 2020-04-01 to 2024-04-01.)
ArticleCitations
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning666
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation477
Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation348
Deep neural network models for computational histopathology: A survey318
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis313
CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation297
PadChest: A large chest x-ray image dataset with multi-label annotated reports269
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis264
Loss odyssey in medical image segmentation240
A survey on active learning and human-in-the-loop deep learning for medical image analysis234
Accurate brain age prediction with lightweight deep neural networks231
Recent advances and clinical applications of deep learning in medical image analysis225
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge213
Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results207
Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks202
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis199
Deep learning for chest X-ray analysis: A survey193
FAT-Net: Feature adaptive transformers for automated skin lesion segmentation184
The Liver Tumor Segmentation Benchmark (LiTS)177
Applications of deep learning in fundus images: A review175
Transformers in medical imaging: A survey166
CS2-Net: Deep learning segmentation of curvilinear structures in 165
Skin lesion segmentation via generative adversarial networks with dual discriminators157
Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study156
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking150
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging150
Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images149
Segmentation of breast ultrasound image with semantic classification of superpixels148
Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan143
Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation139
Models Genesis135
Boundary loss for highly unbalanced segmentation129
Dual-branch combination network (DCN): Towards accurate diagnosis and lesion segmentation of COVID-19 using CT images125
TransMorph: Transformer for unsupervised medical image registration125
A survey on incorporating domain knowledge into deep learning for medical image analysis125
SCS-Net: A Scale and Context Sensitive Network for Retinal Vessel Segmentation113
Head and neck tumor segmentation in PET/CT: The HECKTOR challenge112
Surgical data science – from concepts toward clinical translation111
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images109
AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia106
Supervised learning with cyclegan for low-dose FDG PET image denoising100
CycleMorph: Cycle consistent unsupervised deformable image registration99
Global guidance network for breast lesion segmentation in ultrasound images95
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization94
Federated learning for computational pathology on gigapixel whole slide images94
Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency93
HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images91
Cellular community detection for tissue phenotyping in colorectal cancer histology images90
The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study88
ResGANet: Residual group attention network for medical image classification and segmentation85
Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer85
Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy85
Deep reinforcement learning in medical imaging: A literature review85
EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos83
COVID-AL: The diagnosis of COVID-19 with deep active learning83
BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset82
Rubik’s Cube+: A self-supervised feature learning framework for 3D medical image analysis82
A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification81
Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides81
Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review79
Surgical spectral imaging79
Triple attention learning for classification of 14 thoracic diseases using chest radiography78
Test-time adaptable neural networks for robust medical image segmentation77
Score-based diffusion models for accelerated MRI77
Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks77
A survey on medical image analysis in diabetic retinopathy76
Ms RED: A novel multi-scale residual encoding and decoding network for skin lesion segmentation76
Transformer-based unsupervised contrastive learning for histopathological image classification76
Triple U-net: Hematoxylin-aware nuclei segmentation with progressive dense feature aggregation74
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs73
End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction73
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