Medical Image Analysis

Papers
(The TQCC of Medical Image Analysis is 25. 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 2020-05-01 to 2024-05-01.)
ArticleCitations
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning679
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation487
Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation356
Deep neural network models for computational histopathology: A survey334
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis325
CHAOS Challenge - combined (CT-MR) healthy abdominal organ segmentation309
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis288
PadChest: A large chest x-ray image dataset with multi-label annotated reports279
A survey on active learning and human-in-the-loop deep learning for medical image analysis250
Recent advances and clinical applications of deep learning in medical image analysis249
Loss odyssey in medical image segmentation247
Accurate brain age prediction with lightweight deep neural networks240
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge219
Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results213
BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis212
Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks210
Deep learning for chest X-ray analysis: A survey199
Transformers in medical imaging: A survey195
FAT-Net: Feature adaptive transformers for automated skin lesion segmentation193
The Liver Tumor Segmentation Benchmark (LiTS)192
Applications of deep learning in fundus images: A review185
CS2-Net: Deep learning segmentation of curvilinear structures in 169
Skin lesion segmentation via generative adversarial networks with dual discriminators162
Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study158
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging157
Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images153
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking151
Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan144
Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation144
Models Genesis141
TransMorph: Transformer for unsupervised medical image registration138
A survey on incorporating domain knowledge into deep learning for medical image analysis131
Boundary loss for highly unbalanced segmentation131
Dual-branch combination network (DCN): Towards accurate diagnosis and lesion segmentation of COVID-19 using CT images126
SCS-Net: A Scale and Context Sensitive Network for Retinal Vessel Segmentation122
Surgical data science – from concepts toward clinical translation116
Head and neck tumor segmentation in PET/CT: The HECKTOR challenge114
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images112
AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia108
Supervised learning with cyclegan for low-dose FDG PET image denoising102
CycleMorph: Cycle consistent unsupervised deformable image registration102
Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency101
Federated learning for computational pathology on gigapixel whole slide images100
Global guidance network for breast lesion segmentation in ultrasound images97
HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images96
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization95
The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study93
Transformer-based unsupervised contrastive learning for histopathological image classification92
Cellular community detection for tissue phenotyping in colorectal cancer histology images92
EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos91
Deep reinforcement learning in medical imaging: A literature review91
ResGANet: Residual group attention network for medical image classification and segmentation90
Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer88
COVID-AL: The diagnosis of COVID-19 with deep active learning87
Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides86
BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset86
Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy85
A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification85
Surgical spectral imaging85
Rubik’s Cube+: A self-supervised feature learning framework for 3D medical image analysis85
Score-based diffusion models for accelerated MRI85
Ms RED: A novel multi-scale residual encoding and decoding network for skin lesion segmentation82
Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review81
A survey on medical image analysis in diabetic retinopathy80
Triple attention learning for classification of 14 thoracic diseases using chest radiography80
Test-time adaptable neural networks for robust medical image segmentation79
Triple U-net: Hematoxylin-aware nuclei segmentation with progressive dense feature aggregation77
A Framework for the generation of digital twins of cardiac electrophysiology from clinical 12-leads ECGs77
End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction75
Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning75
Analysis of the ISIC image datasets: Usage, benchmarks and recommendations74
mustGAN: multi-stream Generative Adversarial Networks for MR Image Synthesis73
MSCS-DeepLN: Evaluating lung nodule malignancy using multi-scale cost-sensitive neural networks73
Segment anything model for medical image analysis: An experimental study73
TSegNet: An efficient and accurate tooth segmentation network on 3D dental model72
Yottixel – An Image Search Engine for Large Archives of Histopathology Whole Slide Images71
DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images71
Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification71
Boundary-aware context neural network for medical image segmentation70
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy70
Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology69
Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease69
NuClick: A deep learning framework for interactive segmentation of microscopic images68
AIforCOVID: Predicting the clinical outcomes in patients with COVID-19 applying AI to chest-X-rays. An Italian multicentre study66
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives64
Selective synthetic augmentation with HistoGAN for improved histopathology image classification63
Unsupervised brain imaging 3D anomaly detection and segmentation with transformers62
Hierarchical graph representations in digital pathology62
Detect and correct bias in multi-site neuroimaging datasets62
Multi-task vision transformer using low-level chest X-ray feature corpus for COVID-19 diagnosis and severity quantification62
Capsules for biomedical image segmentation62
CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification61
Diffusion models in medical imaging: A comprehensive survey61
Deep white matter analysis (DeepWMA): Fast and consistent tractography segmentation61
Deep virtual adversarial self-training with consistency regularization for semi-supervised medical image classification60
Semi-supervised task-driven data augmentation for medical image segmentation60
BIAS: Transparent reporting of biomedical image analysis challenges59
Detection, segmentation, simulation and visualization of aortic dissections: A review59
A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set58
Self-supervised driven consistency training for annotation efficient histopathology image analysis58
Graph convolution network with similarity awareness and adaptive calibration for disease-induced deterioration prediction58
Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan57
Marginal loss and exclusion loss for partially supervised multi-organ segmentation56
RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval56
Deep learning for bone marrow cell detection and classification on whole-slide images56
SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining55
Subsampled brain MRI reconstruction by generative adversarial neural networks55
PAIP 2019: Liver cancer segmentation challenge54
Tripartite-GAN: Synthesizing liver contrast-enhanced MRI to improve tumor detection54
FocusNetv2: Imbalanced large and small organ segmentation with adversarial shape constraint for head and neck CT images54
Fully transformer network for skin lesion analysis54
Integrative analysis for COVID-19 patient outcome prediction53
Recent advances in medical image processing for the evaluation of chronic kidney disease53
Automatic labeling of cortical sulci using patch- or CNN-based segmentation techniques combined with bottom-up geometric constraints53
Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images52
ELNet:Automatic classification and segmentation for esophageal lesions using convolutional neural network52
MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning52
Roto-translation equivariant convolutional networks: Application to histopathology image analysis52
Unsupervised lesion detection via image restoration with a normative prior52
Automatic ischemic stroke lesion segmentation from computed tomography perfusion images by image synthesis and attention-based deep neural networks52
Multi-scale fully convolutional neural networks for histopathology image segmentation: From nuclear aberrations to the global tissue architecture51
Hypergraph learning for identification of COVID-19 with CT imaging51
COVID-19 lung infection segmentation with a novel two-stage cross-domain transfer learning framework51
Structured layer surface segmentation for retina OCT using fully convolutional regression networks50
Predicting the progression of mild cognitive impairment using machine learning: A systematic, quantitative and critical review50
Rendezvous: Attention mechanisms for the recognition of surgical action triplets in endoscopic videos50
Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping50
Residual cyclegan for robust domain transformation of histopathological tissue slides49
Image computing for fibre-bundle endomicroscopy: A review49
Towards multi-center glaucoma OCT image screening with semi-supervised joint structure and function multi-task learning48
Self-co-attention neural network for anatomy segmentation in whole breast ultrasound48
DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer48
Semi-supervised WCE image classification with adaptive aggregated attention48
Expert-validated estimation of diagnostic uncertainty for deep neural networks in diabetic retinopathy detection48
Deep metric learning-based image retrieval system for chest radiograph and its clinical applications in COVID-1947
Ultrasound image reconstruction from plane wave radio-frequency data by self-supervised deep neural network47
Incomplete multi-modal representation learning for Alzheimer’s disease diagnosis47
Automated interpretation of congenital heart disease from multi-view echocardiograms47
ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans47
Deep learning for predicting COVID-19 malignant progression46
Unsupervised X-ray image segmentation with task driven generative adversarial networks46
Trophectoderm segmentation in human embryo images via inceptioned U-Net46
Cascaded convolutional networks for automatic cephalometric landmark detection45
Mutual consistency learning for semi-supervised medical image segmentation45
ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate45
Deep learning uncertainty and confidence calibration for the five-class polyp classification from colonoscopy45
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 healthcare45
Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study45
VR-Caps: A Virtual Environment for Capsule Endoscopy44
Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI44
A review on deep-learning algorithms for fetal ultrasound-image analysis44
Directional-TV algorithm for image reconstruction from limited-angular-range data44
Multi-constraint generative adversarial network for dose prediction in radiotherapy44
Synthesized 7T MRI from 3T MRI via deep learning in spatial and wavelet domains44
Automated diagnosis of bone metastasis based on multi-view bone scans using attention-augmented deep neural networks43
SlideGraph+: Whole slide image level graphs to predict HER2 statu43
A novel attention-guided convolutional network for the detection of abnormal cervical cells in cervical cancer screening43
Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography43
Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation43
DeepTarget: Gross tumor and clinical target volume segmentation in esophageal cancer radiotherapy43
GCTI-SN: Geometry-inspired chemical and tissue invariant stain normalization of microscopic medical images43
Deep metric learning for otitis media classification42
Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis42
Mitosis domain generalization in histopathology images — The MIDOG challenge42
Modality alignment contrastive learning for severity assessment of COVID-19 from lung ultrasound and clinical information42
Disentangle domain features for cross-modality cardiac image segmentation42
A deep learning framework for quality assessment and restoration in video endoscopy42
SSA-Net: Spatial self-attention network for COVID-19 pneumonia infection segmentation with semi-supervised few-shot learning42
Self-Supervised monocular depth and ego-Motion estimation in endoscopy: Appearance flow to the rescue41
Contrast agent-free synthesis and segmentation of ischemic heart disease images using progressive sequential causal GANs41
Toward real-time polyp detection using fully CNNs for 2D Gaussian shapes prediction41
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation41
Fast and Low-GPU-memory abdomen CT organ segmentation: The FLARE challenge41
Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis41
A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning40
Computer aided diagnosis of thyroid nodules based on the devised small-datasets multi-view ensemble learning40
DuDoDR-Net: Dual-domain data consistent recurrent network for simultaneous sparse view and metal artifact reduction in computed tomography40
Volumetric memory network for interactive medical image segmentation39
Detection, segmentation, and 3D pose estimation of surgical tools using convolutional neural networks and algebraic geometry39
Uncertainty-aware domain alignment for anatomical structure segmentation39
Mitotic nuclei analysis in breast cancer histopathology images using deep ensemble classifier39
Deep Fusion of Brain Structure-Function in Mild Cognitive Impairment39
Utility of optical see-through head mounted displays in augmented reality-assisted surgery: A systematic review39
Knowledge matters: Chest radiology report generation with general and specific knowledge39
Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis39
CNN-based lung CT registration with multiple anatomical constraints39
Quantifying Parkinson’s disease motor severity under uncertainty using MDS-UPDRS videos39
CaDIS: Cataract dataset for surgical RGB-image segmentation38
A deep-learning approach for direct whole-heart mesh reconstruction38
RA-GCN: Graph convolutional network for disease prediction problems with imbalanced data38
SCPM-Net: An anchor-free 3D lung nodule detection network using sphere representation and center points matching38
Deeply-supervised density regression for automatic cell counting in microscopy images38
Autoencoder based self-supervised test-time adaptation for medical image analysis38
Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: An experiment on prostate histopathology image classification38
Image reconstruction with low-rankness and self-consistency of k-space data in parallel MRI37
Multi-task multi-modal learning for joint diagnosis and prognosis of human cancers37
Deep learning-guided estimation of attenuation correction factors from time-of-flight PET emission data37
Adversarial attack vulnerability of medical image analysis systems: Unexplored factors36
Personalising left-ventricular biophysical models of the heart using parametric physics-informed neural networks36
Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network36
SoftSeg: Advantages of soft versus binary training for image segmentation36
A novel CERNNE approach for predicting Parkinson’s Disease-associated genes and brain regions based on multimodal imaging genetics data36
Anatomy-guided multimodal registration by learning segmentation without ground truth: Application to intraprocedural CBCT/MR liver segmentation and registration36
Integrating uncertainty in deep neural networks for MRI based stroke analysis36
Deep low-Rank plus sparse network for dynamic MR imaging35
Public Covid-19 X-ray datasets and their impact on model bias – A systematic review of a significant problem35
CycleGAN denoising of extreme low-dose cardiac CT using wavelet-assisted noise disentanglement35
AGE challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography35
FusionM4Net: A multi-stage multi-modal learning algorithm for multi-label skin lesion classification35
Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes35
Super-Resolution of Cardiac MR Cine Imaging using Conditional GANs and Unsupervised Transfer Learning34
A unified framework for multimodal structure–function mapping based on eigenmodes34
Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge34
Brain functional connectivity analysis based on multi-graph fusion34
Deep triplet hashing network for case-based medical image retrieval34
Source free domain adaptation for medical image segmentation with fourier style mining33
Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers33
Biomechanically constrained non-rigid MR-TRUS prostate registration using deep learning based 3D point cloud matching33
EIS-Net: Segmenting early infarct and scoring ASPECTS simultaneously on non-contrast CT of patients with acute ischemic stroke33
Multi-level semantic adaptation for few-shot segmentation on cardiac image sequences33
Discriminative ensemble learning for few-shot chest x-ray diagnosis32
AtrialJSQnet: A New framework for joint segmentation and quantification of left atrium and scars incorporating spatial and shape information32
The HoloLens in medicine: A systematic review and taxonomy32
Self-paced and self-consistent co-training for semi-supervised image segmentation32
Adversarial multimodal fusion with attention mechanism for skin lesion classification using clinical and dermoscopic images32
Guidelines and evaluation of clinical explainable AI in medical image analysis32
Diverse data augmentation for learning image segmentation with cross-modality annotations32
United adversarial learning for liver tumor segmentation and detection of multi-modality non-contrast MRI32
MB-FSGAN: Joint segmentation and quantification of kidney tumor on CT by the multi-branch feature sharing generative adversarial network32
Automatic skull defect restoration and cranial implant generation for cranioplasty32
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels32
A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy31
Consolidated domain adaptive detection and localization framework for cross-device colonoscopic images31
Multi-layer pseudo-supervision for histopathology tissue semantic segmentation using patch-level classification labels31
End-to-end multimodal image registration via reinforcement learning31
Weakly-Supervised teacher-Student network for liver tumor segmentation from non-enhanced images30
Longitudinal self-supervised learning30
Multi-scale semi-supervised clustering of brain images: Deriving disease subtypes30
Adaptive diffusion priors for accelerated MRI reconstruction30
Robust deep learning-based semantic organ segmentation in hyperspectral images30
SSMD: Semi-Supervised medical image detection with adaptive consistency and heterogeneous perturbation30
MommiNet-v2: Mammographic multi-view mass identification networks30
Spine-transformers: Vertebra labeling and segmentation in arbitrary field-of-view spine CTs via 3D transformers30
PDAtt-Unet: Pyramid Dual-Decoder Attention Unet for Covid-19 infection segmentation from CT-scans30
Multi-stage learning for segmentation of aortic dissections using a prior aortic anatomy simplification30
A disentangled generative model for disease decomposition in chest X-rays via normal image synthesis30
A hybrid network for automatic hepatocellular carcinoma segmentation in H&E-stained whole slide images30
DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system30
Multi-channel attention-fusion neural network for brain age estimation: Accuracy, generality, and interpretation with 16,705 healthy MRIs across lifespan30
Differentiable neural architecture search for optimal spatial/temporal brain function network decomposition29
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