{"total":197,"rows":[{"id":"2402.02491","title":"VM-UNet: Vision Mamba UNet for Medical Image Segmentation","created":"2024-02-04","cited_by_count":287,"area":"ssm"},{"id":"2201.09873","title":"Transformers in Medical Imaging: A Survey","created":"2022-01-24","cited_by_count":245,"area":null},{"id":"2211.14830","title":"Medical Image Segmentation Review: The success of U-Net","created":"2022-11-27","cited_by_count":191,"area":null},{"id":"2111.11843","title":"U-shape Transformer for Underwater Image Enhancement","created":"2021-11-23","cited_by_count":112,"area":null},{"id":"2206.14718","title":"LViT: Language meets Vision Transformer in Medical Image Segmentation","created":"2022-06-29","cited_by_count":111,"area":null},{"id":"2306.06370","title":"AutoSAM: Adapting SAM to Medical Images by Overloading the Prompt Encoder","created":"2023-06-10","cited_by_count":70,"area":null},{"id":"2405.06880","title":"EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation","created":"2024-05-11","cited_by_count":64,"area":null},{"id":"2401.15583","title":"SCTransNet: Spatial-channel Cross Transformer Network for Infrared Small Target Detection","created":"2024-01-28","cited_by_count":62,"area":null},{"id":"2304.09324","title":"Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets","created":"2023-04-18","cited_by_count":45,"area":null},{"id":"2202.00972","title":"DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation","created":"2022-02-02","cited_by_count":37,"area":null},{"id":"2403.01818","title":"AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic Segmentation","created":"2024-03-04","cited_by_count":35,"area":null},{"id":"2411.03670","title":"Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?","created":"2024-11-06","cited_by_count":31,"area":null},{"id":"2404.02845","title":"Cross-Modal Conditioned Reconstruction for Language-guided Medical Image Segmentation","created":"2024-04-03","cited_by_count":28,"area":null},{"id":"2308.13680","title":"ACC-UNet: A Completely Convolutional UNet model for the 2020s","created":"2023-08-25","cited_by_count":26,"area":null},{"id":"2401.13220","title":"Segment Any Cell: A SAM-based Auto-prompting Fine-tuning Framework for Nuclei Segmentation","created":"2024-01-24","cited_by_count":24,"area":null},{"id":"2212.11677","title":"DuAT: Dual-Aggregation Transformer Network for Medical Image Segmentation","created":"2022-12-21","cited_by_count":22,"area":null},{"id":"2310.16175","title":"G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D Medical Image Segmentation","created":"2023-10-24","cited_by_count":21,"area":null},{"id":"2406.14896","title":"SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation","created":"2024-06-21","cited_by_count":18,"area":null},{"id":"2402.17246","title":"SDR-Former: A Siamese Dual-Resolution Transformer for Liver Lesion Classification Using 3D Multi-Phase Imaging","created":"2024-02-27","cited_by_count":17,"area":null},{"id":"2404.18444","title":"U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models","created":"2024-04-29","cited_by_count":17,"area":"diffusion"},{"id":"2310.12570","title":"DA-TransUNet: Integrating Spatial and Channel Dual Attention with Transformer U-Net for Medical Image Segmentation","created":"2023-10-19","cited_by_count":16,"area":null},{"id":"2312.04727","title":"E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation","created":"2023-12-07","cited_by_count":16,"area":null},{"id":"2206.06665","title":"Online Easy Example Mining for Weakly-supervised Gland Segmentation from Histology Images","created":"2022-06-14","cited_by_count":15,"area":null},{"id":"2303.17696","title":"Dual Cross-Attention for Medical Image Segmentation","created":"2023-03-30","cited_by_count":15,"area":null},{"id":"2503.15949","title":"CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention","created":"2025-03-20","cited_by_count":15,"area":null},{"id":"2308.02959","title":"DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation","created":"2023-08-05","cited_by_count":12,"area":"diffusion"},{"id":"2408.05815","title":"HySparK: Hybrid Sparse Masking for Large Scale Medical Image Pre-Training","created":"2024-08-11","cited_by_count":12,"area":null},{"id":"2304.06662","title":"Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions","created":"2023-04-13","cited_by_count":11,"area":null},{"id":"2308.05695","title":"Masked Diffusion as Self-supervised Representation Learner","created":"2023-08-10","cited_by_count":11,"area":"diffusion"},{"id":"2311.16447","title":"Semi-supervised Segmentation of Histopathology Images with Noise-Aware Topological Consistency","created":"2023-11-28","cited_by_count":11,"area":null},{"id":"2207.14552","title":"ScaleFormer: Revisiting the Transformer-based Backbones from a Scale-wise Perspective for Medical Image Segmentation","created":"2022-07-29","cited_by_count":10,"area":null},{"id":"2306.10364","title":"Residual Spatial Fusion Network for RGB-Thermal Semantic Segmentation","created":"2023-06-17","cited_by_count":10,"area":null},{"id":"2502.05091","title":"DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions","created":"2025-02-07","cited_by_count":10,"area":"mllm"},{"id":"2502.06895","title":"A Comprehensive Review of U-Net and Its Variants: Advances and Applications in Medical Image Segmentation","created":"2025-02-09","cited_by_count":10,"area":null},{"id":"2208.06643","title":"Recent Progress in Transformer-based Medical Image Analysis","created":"2022-08-13","cited_by_count":9,"area":null},{"id":"2305.17937","title":"Attention Mechanisms in Medical Image Segmentation: A Survey","created":"2023-05-29","cited_by_count":9,"area":null},{"id":"2312.10585","title":"ESDMR-Net: A Lightweight Network With Expand-Squeeze and Dual Multiscale Residual Connections for Medical Image Segmentation","created":"2023-12-17","cited_by_count":9,"area":null},{"id":"2312.15182","title":"Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation","created":"2023-12-23","cited_by_count":9,"area":null},{"id":"2405.17520","title":"Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images","created":"2024-05-27","cited_by_count":9,"area":null},{"id":"2210.14007","title":"MEW-UNet: Multi-axis representation learning in frequency domain for medical image segmentation","created":"2022-10-25","cited_by_count":8,"area":null},{"id":"2302.09785","title":"Towards Simultaneous Segmentation of Liver Tumors and Intrahepatic Vessels via Cross-attention Mechanism","created":"2023-02-20","cited_by_count":8,"area":null},{"id":"2305.08396","title":"MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation","created":"2023-05-15","cited_by_count":8,"area":null},{"id":"2406.00341","title":"DSCA: A Digital Subtraction Angiography Sequence Dataset and Spatio-Temporal Model for Cerebral Artery Segmentation","created":"2024-06-01","cited_by_count":8,"area":null},{"id":"2303.00279","title":"Coarse-to-Fine Covid-19 Segmentation via Vision-Language Alignment","created":"2023-03-01","cited_by_count":7,"area":null},{"id":"2501.08458","title":"RWKV-UNet: Improving UNet with Long-Range Cooperation for Effective Medical Image Segmentation","created":"2025-01-14","cited_by_count":7,"area":null},{"id":"2502.14168","title":"Deep learning based infrared small object segmentation: Challenges and future directions","created":"2025-02-20","cited_by_count":7,"area":null},{"id":"2506.18034","title":"Pre-Trained LLM is a Semantic-Aware and Generalizable Segmentation Booster","created":"2025-06-22","cited_by_count":7,"area":null},{"id":"2304.01401","title":"U-Netmer: U-Net meets Transformer for medical image segmentation","created":"2023-04-03","cited_by_count":6,"area":null},{"id":"2309.16661","title":"SA2-Net: Scale-aware Attention Network for Microscopic Image Segmentation","created":"2023-09-28","cited_by_count":6,"area":null},{"id":"2403.18198","title":"Generative Medical Segmentation","created":"2024-03-27","cited_by_count":6,"area":null},{"id":"2406.19749","title":"SPIRONet: Spatial-Frequency Learning and Graph-based Channel Interaction Network for Vessel Segmentation","created":"2024-06-28","cited_by_count":6,"area":null},{"id":"2408.12815","title":"Staircase Cascaded Fusion of Lightweight Local Pattern Recognition and Long-Range Dependencies for Structural Crack Segmentation","created":"2024-08-23","cited_by_count":6,"area":null},{"id":"2408.13698","title":"CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation","created":"2024-08-25","cited_by_count":6,"area":null},{"id":"2409.14676","title":"TransUKAN:Computing-Efficient Hybrid KAN-Transformer for Enhanced Medical Image Segmentation","created":"2024-09-23","cited_by_count":6,"area":null},{"id":"2410.15036","title":"EViT-Unet: U-Net Like Efficient Vision Transformer for Medical Image Segmentation on Mobile and Edge Devices","created":"2024-10-19","cited_by_count":6,"area":null},{"id":"2504.01561","title":"STPNet: Scale-aware Text Prompt Network for Medical Image Segmentation","created":"2025-04-02","cited_by_count":6,"area":null},{"id":"2508.01064","title":"Mobile U-ViT: Revisiting large kernel and U-shaped ViT for efficient medical image segmentation","created":"2025-08-01","cited_by_count":6,"area":null},{"id":"2312.08866","title":"MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis Attention","created":"2023-12-14","cited_by_count":5,"area":null},{"id":"2403.18637","title":"Transformers-based architectures for stroke segmentation: A review","created":"2024-03-27","cited_by_count":5,"area":null},{"id":"2407.07441","title":"HAFormer: Unleashing the Power of Hierarchy-Aware Features for Lightweight Semantic Segmentation","created":"2024-07-10","cited_by_count":5,"area":null},{"id":"2503.06748","title":"DiffAtlas: GenAI-fying Atlas Segmentation via Image-Mask Diffusion","created":"2025-03-09","cited_by_count":5,"area":null},{"id":"2505.18423","title":"CENet: Context Enhancement Network for Medical Image Segmentation","created":"2025-05-23","cited_by_count":5,"area":null},{"id":"2602.14498","title":"Uncertainty-Aware Vision-Language Segmentation for Medical Imaging","created":"2026-02-16","cited_by_count":5,"area":null},{"id":"2304.07724","title":"MS-LSTM: Exploring Spatiotemporal Multiscale Representations in Video Prediction Domain","created":"2023-04-16","cited_by_count":4,"area":null},{"id":"2308.08283","title":"CARE: A Large Scale CT Image Dataset and Clinical Applicable Benchmark Model for Rectal Cancer Segmentation","created":"2023-08-16","cited_by_count":4,"area":null},{"id":"2403.15901","title":"MatchSeg: Towards Better Segmentation via Reference Image Matching","created":"2024-03-23","cited_by_count":4,"area":null},{"id":"2411.15076","title":"RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency","created":"2024-11-22","cited_by_count":4,"area":null},{"id":"2411.15274","title":"Feature-interactive Siamese graph encoder-based image analysis to predict STAS from histopathology images in lung cancer","created":"2024-11-22","cited_by_count":4,"area":null},{"id":"2501.01618","title":"Merging Context Clustering with Visual State Space Models for Medical Image Segmentation","created":"2025-01-03","cited_by_count":4,"area":null},{"id":"2503.23422","title":"Improving underwater semantic segmentation with underwater image quality attention and muti-scale aggregation attention","created":"2025-03-30","cited_by_count":4,"area":null},{"id":"2504.14737","title":"SuperCL: Superpixel Guided Contrastive Learning for Medical Image Segmentation Pre-training","created":"2025-04-20","cited_by_count":4,"area":null},{"id":"2506.18335","title":"Rethinking Decoder Design: Improving Biomarker Segmentation Using Depth-to-Space Restoration and Residual Linear Attention","created":"2025-06-23","cited_by_count":4,"area":null},{"id":"2509.19719","title":"Frequency-domain Multi-modal Fusion for Language-guided Medical Image Segmentation","created":"2025-09-24","cited_by_count":4,"area":null},{"id":"2303.00232","title":"Towards more precise automatic analysis: a comprehensive survey of deep learning-based multi-organ segmentation","created":"2023-03-01","cited_by_count":3,"area":null},{"id":"2304.00749","title":"Small but Mighty: Enhancing 3D Point Clouds Semantic Segmentation with U-Next Framework","created":"2023-04-03","cited_by_count":3,"area":null},{"id":"2304.04614","title":"HST-MRF: Heterogeneous Swin Transformer with Multi-Receptive Field for Medical Image Segmentation","created":"2023-04-10","cited_by_count":3,"area":null},{"id":"2304.11905","title":"Data-driven Knowledge Fusion for Deep Multi-instance Learning","created":"2023-04-24","cited_by_count":3,"area":null},{"id":"2307.00174","title":"Multiscale Progressive Text Prompt Network for Medical Image Segmentation","created":"2023-06-30","cited_by_count":3,"area":null},{"id":"2307.01979","title":"ToothSegNet: Image Degradation meets Tooth Segmentation in CBCT Images","created":"2023-07-05","cited_by_count":3,"area":null},{"id":"2307.02953","title":"SegNetr: Rethinking the local-global interactions and skip connections in U-shaped networks","created":"2023-07-06","cited_by_count":3,"area":null},{"id":"2307.03388","title":"General-Purpose Multimodal Transformer meets Remote Sensing Semantic Segmentation","created":"2023-07-07","cited_by_count":3,"area":null},{"id":"2309.11876","title":"Multi-level Asymmetric Contrastive Learning for Volumetric Medical Image Segmentation Pre-training","created":"2023-09-21","cited_by_count":3,"area":null},{"id":"2312.17030","title":"Learning Multi-axis Representation in Frequency Domain for Medical Image Segmentation","created":"2023-12-28","cited_by_count":3,"area":null},{"id":"2402.08276","title":"Rethinking U-net Skip Connections for Biomedical Image Segmentation","created":"2024-02-13","cited_by_count":3,"area":null},{"id":"2404.00122","title":"AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation","created":"2024-03-29","cited_by_count":3,"area":null},{"id":"2404.00231","title":"Attention-based Shape-Deformation Networks for Artifact-Free Geometry Reconstruction of Lumbar Spine from MR Images","created":"2024-03-30","cited_by_count":3,"area":null},{"id":"2404.18199","title":"Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical Imaging","created":"2024-04-28","cited_by_count":3,"area":null},{"id":"2406.16993","title":"Are Vision xLSTM Embedded UNet More Reliable in Medical 3D Image Segmentation?","created":"2024-06-24","cited_by_count":3,"area":null},{"id":"2512.03834","title":"Lean Unet: A Compact Model for Image Segmentation","created":"2025-12-03","cited_by_count":3,"area":null},{"id":"2306.13592","title":"TACOformer:Token-channel compounded Cross Attention for Multimodal Emotion Recognition","created":"2023-06-23","cited_by_count":2,"area":null},{"id":"2308.02161","title":"M2Former: Multi-Scale Patch Selection for Fine-Grained Visual Recognition","created":"2023-08-04","cited_by_count":2,"area":null},{"id":"2310.10951","title":"FusionU-Net: U-Net with Enhanced Skip Connection for Pathology Image Segmentation","created":"2023-10-17","cited_by_count":2,"area":null},{"id":"2401.11856","title":"MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentation","created":"2024-01-22","cited_by_count":2,"area":null},{"id":"2402.03230","title":"Architecture Analysis and Benchmarking of 3D U-shaped Deep Learning Models for Thoracic Anatomical Segmentation","created":"2024-02-05","cited_by_count":2,"area":null},{"id":"2403.02566","title":"Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware Learning","created":"2024-03-05","cited_by_count":2,"area":null},{"id":"2405.04169","title":"D-TrAttUnet: Toward Hybrid CNN-Transformer Architecture for Generic and Subtle Segmentation in Medical Images","created":"2024-05-07","cited_by_count":2,"area":null},{"id":"2407.13920","title":"DuoFormer: Leveraging Hierarchical Visual Representations by Local and Global Attention","created":"2024-07-18","cited_by_count":2,"area":null},{"id":"2407.18097","title":"SSTD: Stripe-Like Space Target Detection Using Single-Point Weak Supervision","created":"2024-07-25","cited_by_count":2,"area":null},{"id":"2411.02935","title":"A High Resolution Urban and Rural Settlement Map of Africa Using Deep Learning and Satellite Imagery","created":"2024-11-05","cited_by_count":2,"area":null},{"id":"2412.01405","title":"MambaU-Lite: A Lightweight Model based on Mamba and Integrated Channel-Spatial Attention for Skin Lesion Segmentation","created":"2024-12-02","cited_by_count":2,"area":"ssm"}],"next_cursor":"100"}