{"total":268,"rows":[{"id":"2201.09873","title":"Transformers in Medical Imaging: A Survey","created":"2022-01-24","cited_by_count":245,"area":null},{"id":"2404.09556","title":"nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation","created":"2024-04-15","cited_by_count":240,"area":null},{"id":"2308.02463","title":"Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data","created":"2023-08-04","cited_by_count":179,"area":null},{"id":"2104.05833","title":"Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization","created":"2021-04-12","cited_by_count":141,"area":null},{"id":"2401.10815","title":"Exploring scalable medical image encoders beyond text supervision","created":"2024-01-19","cited_by_count":132,"area":null},{"id":"2111.12525","title":"Causality-inspired Single-source Domain Generalization for Medical Image Segmentation","created":"2021-11-24","cited_by_count":119,"area":null},{"id":"2102.04525","title":"Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation","created":"2021-02-08","cited_by_count":88,"area":null},{"id":"2108.00622","title":"Recurrent Mask Refinement for Few-Shot Medical Image Segmentation","created":"2021-08-02","cited_by_count":63,"area":null},{"id":"2304.05396","title":"SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model","created":"2023-04-10","cited_by_count":61,"area":null},{"id":"2106.09157","title":"Positional Contrastive Learning for Volumetric Medical Image Segmentation","created":"2021-06-16","cited_by_count":56,"area":null},{"id":"2105.05874","title":"The Federated Tumor Segmentation (FeTS) Challenge","created":"2021-05-12","cited_by_count":50,"area":null},{"id":"2307.13125","title":"Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review","created":"2023-07-24","cited_by_count":48,"area":null},{"id":"2403.18271","title":"Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding","created":"2024-03-27","cited_by_count":48,"area":null},{"id":"2310.06873","title":"A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods","created":"2023-10-09","cited_by_count":39,"area":null},{"id":"2103.05115","title":"Deep reinforcement learning in medical imaging: A literature review","created":"2021-03-05","cited_by_count":34,"area":null},{"id":"2312.05391","title":"Loss Functions in the Era of Semantic Segmentation: A Survey and Outlook","created":"2023-12-08","cited_by_count":34,"area":null},{"id":"2304.13973","title":"SkinSAM: Empowering Skin Cancer Segmentation with Segment Anything Model","created":"2023-04-27","cited_by_count":32,"area":null},{"id":"2404.10156","title":"SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation","created":"2024-04-15","cited_by_count":31,"area":null},{"id":"2104.02847","title":"Deep Implicit Statistical Shape Models for 3D Medical Image Delineation","created":"2021-04-07","cited_by_count":26,"area":null},{"id":"2106.10637","title":"More than Encoder: Introducing Transformer Decoder to Upsample","created":"2021-06-20","cited_by_count":26,"area":null},{"id":"2209.00183","title":"ProCo: Prototype-aware Contrastive Learning for Long-tailed Medical Image Classification","created":"2022-09-01","cited_by_count":25,"area":null},{"id":"2509.02379","title":"MedDINOv3: How to adapt vision foundation models for medical image segmentation?","created":"2025-09-02","cited_by_count":25,"area":null},{"id":"2208.11451","title":"Q-Net: Query-Informed Few-Shot Medical Image Segmentation","created":"2022-08-24","cited_by_count":24,"area":null},{"id":"2107.12689","title":"A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR","created":"2021-07-27","cited_by_count":21,"area":null},{"id":"2109.12271","title":"BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation","created":"2021-09-25","cited_by_count":19,"area":null},{"id":"2108.04543","title":"Known Operator Learning and Hybrid Machine Learning in Medical Imaging -- A Review of the Past, the Present, and the Future","created":"2021-08-10","cited_by_count":18,"area":null},{"id":"2103.10178","title":"A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation","created":"2021-03-18","cited_by_count":17,"area":null},{"id":"2105.01218","title":"Weakly-Supervised Universal Lesion Segmentation with Regional Level Set Loss","created":"2021-05-03","cited_by_count":16,"area":null},{"id":"2105.12722","title":"Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning","created":"2021-05-26","cited_by_count":16,"area":null},{"id":"2304.00212","title":"Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization","created":"2023-04-01","cited_by_count":16,"area":null},{"id":"2203.15163","title":"CAT-Net: A Cross-Slice Attention Transformer Model for Prostate Zonal Segmentation in MRI","created":"2022-03-29","cited_by_count":15,"area":null},{"id":"2107.04263","title":"Towards Robust General Medical Image Segmentation","created":"2021-07-09","cited_by_count":14,"area":null},{"id":"2109.00374","title":"ImageTBAD: A 3D Computed Tomography Angiography Image Dataset for Automatic Segmentation of Type-B Aortic Dissection","created":"2021-09-01","cited_by_count":14,"area":null},{"id":"2208.12776","title":"SFusion: Self-attention based N-to-One Multimodal Fusion Block","created":"2022-08-26","cited_by_count":14,"area":null},{"id":"2208.06449","title":"When CNN Meet with ViT: Towards Semi-Supervised Learning for Multi-Class Medical Image Semantic Segmentation","created":"2022-08-12","cited_by_count":13,"area":null},{"id":"2209.07193","title":"Rethinking the Unpretentious U-net for Medical Ultrasound Image Segmentation","created":"2022-09-15","cited_by_count":13,"area":null},{"id":"2303.10894","title":"M$^{2}$SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation","created":"2023-03-20","cited_by_count":13,"area":null},{"id":"2308.00220","title":"Boundary Difference Over Union Loss For Medical Image Segmentation","created":"2023-08-01","cited_by_count":13,"area":null},{"id":"2406.01591","title":"DeNVeR: Deformable Neural Vessel Representations for Unsupervised Video Vessel Segmentation","created":"2024-06-03","cited_by_count":13,"area":null},{"id":"2101.09321","title":"Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation","created":"2021-01-22","cited_by_count":12,"area":null},{"id":"2103.13314","title":"MONAIfbs: MONAI-based fetal brain MRI deep learning segmentation","created":"2021-03-21","cited_by_count":12,"area":null},{"id":"2201.13078","title":"Lymphoma segmentation from 3D PET-CT images using a deep evidential network","created":"2022-01-31","cited_by_count":12,"area":null},{"id":"2205.11096","title":"FedNorm: Modality-Based Normalization in Federated Learning for Multi-Modal Liver Segmentation","created":"2022-05-23","cited_by_count":12,"area":null},{"id":"2206.11739","title":"Evidence fusion with contextual discounting for multi-modality medical image segmentation","created":"2022-06-23","cited_by_count":12,"area":null},{"id":"2310.19898","title":"MIST: Medical Image Segmentation Transformer with Convolutional Attention Mixing (CAM) Decoder","created":"2023-10-30","cited_by_count":12,"area":null},{"id":"2407.04651","title":"SAM Fewshot Finetuning for Anatomical Segmentation in Medical Images","created":"2024-07-05","cited_by_count":12,"area":null},{"id":"2111.07535","title":"T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imaging","created":"2021-11-15","cited_by_count":11,"area":null},{"id":"2204.08043","title":"Continual Hippocampus Segmentation with Transformers","created":"2022-04-17","cited_by_count":11,"area":null},{"id":"2208.01643","title":"CTooth+: A Large-scale Dental Cone Beam Computed Tomography Dataset and Benchmark for Tooth Volume Segmentation","created":"2022-08-02","cited_by_count":11,"area":null},{"id":"2103.16493","title":"Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training","created":"2021-03-30","cited_by_count":10,"area":null},{"id":"2105.14071","title":"Classification of Brain Tumours in MR Images using Deep Spatiospatial Models","created":"2021-05-28","cited_by_count":10,"area":null},{"id":"2109.01668","title":"How Reliable Are Out-of-Distribution Generalization Methods for Medical Image Segmentation?","created":"2021-09-03","cited_by_count":10,"area":null},{"id":"2201.05344","title":"AWSnet: An Auto-weighted Supervision Attention Network for Myocardial Scar and Edema Segmentation in Multi-sequence Cardiac Magnetic Resonance Images","created":"2022-01-14","cited_by_count":10,"area":null},{"id":"2208.02311","title":"Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers","created":"2022-08-03","cited_by_count":10,"area":null},{"id":"2501.12844","title":"GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation","created":"2025-01-22","cited_by_count":10,"area":null},{"id":"2101.07715","title":"Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms","created":"2021-01-19","cited_by_count":9,"area":null},{"id":"2204.14199","title":"Preoperative brain tumor imaging: models and software for segmentation and standardized reporting","created":"2022-04-29","cited_by_count":9,"area":null},{"id":"2212.09206","title":"Segmentation Ability Map: Interpret deep features for medical image segmentation","created":"2022-12-19","cited_by_count":9,"area":null},{"id":"2310.03967","title":"Sub-token ViT Embedding via Stochastic Resonance Transformers","created":"2023-10-06","cited_by_count":9,"area":null},{"id":"2104.13293","title":"Evidential segmentation of 3D PET/CT images","created":"2021-04-27","cited_by_count":8,"area":null},{"id":"2105.01828","title":"Lesion Segmentation and RECIST Diameter Prediction via Click-driven Attention and Dual-path Connection","created":"2021-05-05","cited_by_count":8,"area":null},{"id":"2111.03368","title":"Hepatic vessel segmentation based on 3D swin-transformer with inductive biased multi-head self-attention","created":"2021-11-05","cited_by_count":8,"area":null},{"id":"2301.02393","title":"Graph Convolution Based Cross-Network Multi-Scale Feature Fusion for Deep Vessel Segmentation","created":"2023-01-06","cited_by_count":7,"area":null},{"id":"2305.12447","title":"BreastSAM: A Study of Segment Anything Model for Breast Tumor Detection in Ultrasound Images","created":"2023-05-21","cited_by_count":7,"area":null},{"id":"2311.04942","title":"CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation","created":"2023-11-08","cited_by_count":7,"area":null},{"id":"2402.14611","title":"Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image Segmentation","created":"2024-02-22","cited_by_count":7,"area":null},{"id":"2603.28589","title":"Towards a Medical AI Scientist","created":"2026-03-30","cited_by_count":7,"area":null},{"id":"2201.06251","title":"Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?","created":"2022-01-17","cited_by_count":6,"area":null},{"id":"2205.08239","title":"CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI","created":"2022-05-17","cited_by_count":6,"area":null},{"id":"2302.07967","title":"Self-supervised Registration and Segmentation of the Ossicles with A Single Ground Truth Label","created":"2023-02-15","cited_by_count":6,"area":null},{"id":"2311.01308","title":"Hybrid-Fusion Transformer for Multisequence MRI","created":"2023-11-02","cited_by_count":6,"area":null},{"id":"2312.05528","title":"Exploring 3D U-Net Training Configurations and Post-Processing Strategies for the MICCAI 2023 Kidney and Tumor Segmentation Challenge","created":"2023-12-09","cited_by_count":6,"area":null},{"id":"2402.06190","title":"Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain","created":"2024-02-09","cited_by_count":6,"area":null},{"id":"2409.06821","title":"Sam2Rad: A Segmentation Model for Medical Images with Learnable Prompts","created":"2024-09-10","cited_by_count":6,"area":null},{"id":"2109.10674","title":"Self-Training Based Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation","created":"2021-09-22","cited_by_count":5,"area":null},{"id":"2205.08257","title":"Detection Masking for Improved OCR on Noisy Documents","created":"2022-05-17","cited_by_count":5,"area":null},{"id":"2301.02554","title":"MSCDA: Multi-level Semantic-guided Contrast Improves Unsupervised Domain Adaptation for Breast MRI Segmentation in Small Datasets","created":"2023-01-04","cited_by_count":5,"area":null},{"id":"2411.05223","title":"Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal Mechanisms","created":"2024-11-07","cited_by_count":5,"area":null},{"id":"2106.10686","title":"Quality-Aware Memory Network for Interactive Volumetric Image Segmentation","created":"2021-06-20","cited_by_count":4,"area":null},{"id":"2111.08480","title":"A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals","created":"2021-11-12","cited_by_count":4,"area":null},{"id":"2205.01733","title":"Application of belief functions to medical image segmentation: A review","created":"2022-05-03","cited_by_count":4,"area":null},{"id":"2208.13113","title":"Accurate and Robust Lesion RECIST Diameter Prediction and Segmentation with Transformers","created":"2022-08-28","cited_by_count":4,"area":null},{"id":"2211.11509","title":"Segmentation, Classification, and Quality Assessment of UW-OCTA Images for the Diagnosis of Diabetic Retinopathy","created":"2022-11-21","cited_by_count":4,"area":null},{"id":"2307.12299","title":"Hybrid-CSR: Coupling Explicit and Implicit Shape Representation for Cortical Surface Reconstruction","created":"2023-07-23","cited_by_count":4,"area":null},{"id":"2311.09614","title":"Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses","created":"2023-11-16","cited_by_count":4,"area":null},{"id":"2312.12990","title":"Multi-task Learning To Improve Semantic Segmentation Of CBCT Scans Using Image Reconstruction","created":"2023-12-20","cited_by_count":4,"area":null},{"id":"2403.05912","title":"Mask-Enhanced Segment Anything Model for Tumor Lesion Semantic Segmentation","created":"2024-03-09","cited_by_count":4,"area":null},{"id":"2404.05584","title":"Neural Cellular Automata for Lightweight, Robust and Explainable Classification of White Blood Cell Images","created":"2024-04-08","cited_by_count":4,"area":null},{"id":"2604.27277","title":"BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning","created":"2026-04-30","cited_by_count":4,"area":null},{"id":"2106.10992","title":"Estimating MRI Image Quality via Image Reconstruction Uncertainty","created":"2021-06-21","cited_by_count":3,"area":null},{"id":"2111.07918","title":"Transformer for Polyp Detection","created":"2021-10-14","cited_by_count":3,"area":null},{"id":"2201.09693","title":"Shape-consistent Generative Adversarial Networks for multi-modal Medical segmentation maps","created":"2022-01-24","cited_by_count":3,"area":null},{"id":"2203.05709","title":"Towards Bi-directional Skip Connections in Encoder-Decoder Architectures and Beyond","created":"2022-03-11","cited_by_count":3,"area":null},{"id":"2207.04721","title":"Hybrid Skip: A Biologically Inspired Skip Connection for the UNet Architecture","created":"2022-07-11","cited_by_count":3,"area":null},{"id":"2210.01485","title":"APAUNet: Axis Projection Attention UNet for Small Target in 3D Medical Segmentation","created":"2022-10-04","cited_by_count":3,"area":null},{"id":"2212.10066","title":"RepMode: Learning to Re-parameterize Diverse Experts for Subcellular Structure Prediction","created":"2022-12-20","cited_by_count":3,"area":null},{"id":"2302.02521","title":"Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor Segmentation","created":"2023-02-06","cited_by_count":3,"area":null},{"id":"2406.11659","title":"Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes","created":"2024-06-17","cited_by_count":3,"area":null},{"id":"2406.17471","title":"Medical Image Segmentation Using Directional Window Attention","created":"2024-06-25","cited_by_count":3,"area":null},{"id":"2409.09796","title":"Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis","created":"2024-09-15","cited_by_count":3,"area":null}],"next_cursor":"100"}