Medical Image Analysis

Papers
(The TQCC of Medical Image Analysis is 26. 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
NuClick: A deep learning framework for interactive segmentation of microscopic images77
Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification77
Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease77
Marginal loss and exclusion loss for partially supervised multi-organ segmentation76
Hierarchical graph representations in digital pathology76
Self-supervised driven consistency training for annotation efficient histopathology image analysis74
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation74
Multi-task vision transformer using low-level chest X-ray feature corpus for COVID-19 diagnosis and severity quantification74
Segment anything model for medical images?73
DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer72
Semi-supervised task-driven data augmentation for medical image segmentation71
Capsules for biomedical image segmentation71
Detect and correct bias in multi-site neuroimaging datasets70
Graph convolution network with similarity awareness and adaptive calibration for disease-induced deterioration prediction70
Selective synthetic augmentation with HistoGAN for improved histopathology image classification70
AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study70
Deep virtual adversarial self-training with consistency regularization for semi-supervised medical image classification69
Deep learning for bone marrow cell detection and classification on whole-slide images67
Detection, segmentation, simulation and visualization of aortic dissections: A review67
Deep white matter analysis (DeepWMA): Fast and consistent tractography segmentation66
FocusNetv2: Imbalanced large and small organ segmentation with adversarial shape constraint for head and neck CT images66
A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set65
Fully transformer network for skin lesion analysis65
Subsampled brain MRI reconstruction by generative adversarial neural networks65
A review on deep-learning algorithms for fetal ultrasound-image analysis64
BIAS: Transparent reporting of biomedical image analysis challenges64
PAIP 2019: Liver cancer segmentation challenge64
Rendezvous: Attention mechanisms for the recognition of surgical action triplets in endoscopic videos63
CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification63
MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning63
Recent advances in medical image processing for the evaluation of chronic kidney disease62
SlideGraph+: Whole slide image level graphs to predict HER2 status61
Structured layer surface segmentation for retina OCT using fully convolutional regression networks61
Automatic ischemic stroke lesion segmentation from computed tomography perfusion images by image synthesis and attention-based deep neural networks60
Multi-scale fully convolutional neural networks for histopathology image segmentation: From nuclear aberrations to the global tissue architecture60
Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images60
Adaptive diffusion priors for accelerated MRI reconstruction59
Volumetric memory network for interactive medical image segmentation58
ELNet:Automatic classification and segmentation for esophageal lesions using convolutional neural network58
Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review58
ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans58
Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan57
Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping57
COVID-19 lung infection segmentation with a novel two-stage cross-domain transfer learning framework57
Cascaded convolutional networks for automatic cephalometric landmark detection56
Multi-constraint generative adversarial network for dose prediction in radiotherapy56
Ultrasound image reconstruction from plane wave radio-frequency data by self-supervised deep neural network56
Hypergraph learning for identification of COVID-19 with CT imaging56
Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis56
ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate55
Integrative analysis for COVID-19 patient outcome prediction55
A novel attention-guided convolutional network for the detection of abnormal cervical cells in cervical cancer screening55
Mitosis domain generalization in histopathology images — The MIDOG challenge55
Residual cyclegan for robust domain transformation of histopathological tissue slides55
Roto-translation equivariant convolutional networks: Application to histopathology image analysis55
A deep learning framework for quality assessment and restoration in video endoscopy54
Dual-stream pyramid registration network54
Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography52
Directional-TV algorithm for image reconstruction from limited-angular-range data52
Incomplete multi-modal representation learning for Alzheimer’s disease diagnosis52
Quantifying Parkinson’s disease motor severity under uncertainty using MDS-UPDRS videos52
Deep metric learning-based image retrieval system for chest radiograph and its clinical applications in COVID-1951
SCPM-Net: An anchor-free 3D lung nodule detection network using sphere representation and center points matching51
FusionM4Net: A multi-stage multi-modal learning algorithm for multi-label skin lesion classification51
Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis51
Knowledge matters: Chest radiology report generation with general and specific knowledge51
Automated interpretation of congenital heart disease from multi-view echocardiograms51
Utility of optical see-through head mounted displays in augmented reality-assisted surgery: A systematic review51
Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI51
Disentangle domain features for cross-modality cardiac image segmentation50
A deep-learning approach for direct whole-heart mesh reconstruction50
Deep Fusion of Brain Structure-Function in Mild Cognitive Impairment50
Source free domain adaptation for medical image segmentation with fourier style mining50
SSA-Net: Spatial self-attention network for COVID-19 pneumonia infection segmentation with semi-supervised few-shot learning50
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels50
Deep low-Rank plus sparse network for dynamic MR imaging49
DeepTarget: Gross tumor and clinical target volume segmentation in esophageal cancer radiotherapy49
Self-Supervised monocular depth and ego-Motion estimation in endoscopy: Appearance flow to the rescue48
The HoloLens in medicine: A systematic review and taxonomy48
VR-Caps: A Virtual Environment for Capsule Endoscopy48
Deep learning for predicting COVID-19 malignant progression48
Position paper on COVID-19 imaging and AI: From the clinical needs and technological challenges to initial AI solutions at the lab and national level towards a new era for AI in healthcare48
Guidelines and evaluation of clinical explainable AI in medical image analysis48
GCTI-SN: Geometry-inspired chemical and tissue invariant stain normalization of microscopic medical images47
Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study47
WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image47
Autoencoder based self-supervised test-time adaptation for medical image analysis47
Modality alignment contrastive learning for severity assessment of COVID-19 from lung ultrasound and clinical information47
CNN-based lung CT registration with multiple anatomical constraints47
Detection, segmentation, and 3D pose estimation of surgical tools using convolutional neural networks and algebraic geometry46
Personalising left-ventricular biophysical models of the heart using parametric physics-informed neural networks46
Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks46
RA-GCN: Graph convolutional network for disease prediction problems with imbalanced data46
Deep metric learning for otitis media classification46
Integrating uncertainty in deep neural networks for MRI based stroke analysis45
DuDoDR-Net: Dual-domain data consistent recurrent network for simultaneous sparse view and metal artifact reduction in computed tomography45
Computer aided diagnosis of thyroid nodules based on the devised small-datasets multi-view ensemble learning45
Toward real-time polyp detection using fully CNNs for 2D Gaussian shapes prediction45
A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning44
MommiNet-v2: Mammographic multi-view mass identification networks44
Mitotic nuclei analysis in breast cancer histopathology images using deep ensemble classifier44
PDAtt-Unet: Pyramid Dual-Decoder Attention Unet for Covid-19 infection segmentation from CT-scans43
CycleGAN denoising of extreme low-dose cardiac CT using wavelet-assisted noise disentanglement43
Adversarial attack vulnerability of medical image analysis systems: Unexplored factors43
Multi-channel attention-fusion neural network for brain age estimation: Accuracy, generality, and interpretation with 16,705 healthy MRIs across lifespan43
CaDIS: Cataract dataset for surgical RGB-image segmentation43
Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image segmentation43
Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification43
Deeply-supervised density regression for automatic cell counting in microscopy images43
SSD-KD: A self-supervised diverse knowledge distillation method for lightweight skin lesion classification using dermoscopic images43
Deep learning for computational cytology: A survey42
EIS-Net: Segmenting early infarct and scoring ASPECTS simultaneously on non-contrast CT of patients with acute ischemic stroke42
Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network42
Multi-task multi-modal learning for joint diagnosis and prognosis of human cancers42
Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge41
SoftSeg: Advantages of soft versus binary training for image segmentation41
Spine-transformers: Vertebra labeling and segmentation in arbitrary field-of-view spine CTs via 3D transformers41
Source-free domain adaptation for image segmentation40
United adversarial learning for liver tumor segmentation and detection of multi-modality non-contrast MRI40
Adversarial multimodal fusion with attention mechanism for skin lesion classification using clinical and dermoscopic images40
A novel CERNNE approach for predicting Parkinson’s Disease-associated genes and brain regions based on multimodal imaging genetics data40
One model is all you need: Multi-task learning enables simultaneous histology image segmentation and classification39
Super-Resolution of Cardiac MR Cine Imaging using Conditional GANs and Unsupervised Transfer Learning39
Automatic skull defect restoration and cranial implant generation for cranioplasty39
Public Covid-19 X-ray datasets and their impact on model bias – A systematic review of a significant problem39
Anatomy-guided multimodal registration by learning segmentation without ground truth: Application to intraprocedural CBCT/MR liver segmentation and registration39
A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy39
Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes39
Robust deep learning-based semantic organ segmentation in hyperspectral images39
Multi-layer pseudo-supervision for histopathology tissue semantic segmentation using patch-level classification labels39
AGE challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography39
Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching39
Deep triplet hashing network for case-based medical image retrieval38
Diverse data augmentation for learning image segmentation with cross-modality annotations38
Brain functional connectivity analysis based on multi-graph fusion38
Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes38
Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers37
DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system37
A survey on deep learning for skin lesion segmentation37
A unified framework for multimodal structure–function mapping based on eigenmodes37
Boundary-rendering network for breast lesion segmentation in ultrasound images37
Dual attention enhancement feature fusion network for segmentation and quantitative analysis of paediatric echocardiography37
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation37
ExplAIn: Explanatory artificial intelligence for diabetic retinopathy diagnosis37
Quantifying and leveraging predictive uncertainty for medical image assessment37
Selective identification and localization of indolent and aggressive prostate cancers via CorrSigNIA: an MRI-pathology correlation and deep learning framework37
Ambiguity-selective consistency regularization for mean-teacher semi-supervised medical image segmentation37
Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images36
AtrialJSQnet: A New framework for joint segmentation and quantification of left atrium and scars incorporating spatial and shape information36
Self-paced and self-consistent co-training for semi-supervised image segmentation36
Dual-path network with synergistic grouping loss and evidence driven risk stratification for whole slide cervical image analysis36
DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentation36
RNNSLAM: Reconstructing the 3D colon to visualize missing regions during a colonoscopy36
Weakly-Supervised teacher-Student network for liver tumor segmentation from non-enhanced images36
A disentangled generative model for disease decomposition in chest X-rays via normal image synthesis36
NENet: Nested EfficientNet and adversarial learning for joint optic disc and cup segmentation36
Discriminative ensemble learning for few-shot chest x-ray diagnosis35
Predicting brain structural network using functional connectivity35
End-to-end multimodal image registration via reinforcement learning35
Multi-level semantic adaptation for few-shot segmentation on cardiac image sequences35
Learning disentangled representations in the imaging domain35
An attention residual u-net with differential preprocessing and geometric postprocessing: Learning how to segment vasculature including intracranial aneurysms35
Towards evaluating the robustness of deep diagnostic models by adversarial attack35
A hybrid network for automatic hepatocellular carcinoma segmentation in H&E-stained whole slide images35
Dynamic MRI reconstruction with end-to-end motion-guided network34
Does your dermatology classifier know what it doesn’t know? Detecting the long-tail of unseen conditions34
Weakly supervised object detection with 2D and 3D regression neural networks34
3D vessel-like structure segmentation in medical images by an edge-reinforced network34
Longitudinal self-supervised learning34
Consolidated domain adaptive detection and localization framework for cross-device colonoscopic images34
A semi-supervised multi-task learning framework for cancer classification with weak annotation in whole-slide images34
Modeling dynamic characteristics of brain functional connectivity networks using resting-state functional MRI33
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