{"list":"other","total":52,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"2105.05233","title":"Diffusion Models Beat GANs on Image Synthesis","created":"2021-05-11","cited_by_count":8255},{"id":"1611.07004","title":"Image-to-Image Translation with Conditional Adversarial Networks","created":"2016-11-21","cited_by_count":4527},{"id":"1711.07971","title":"Non-local Neural Networks","created":"2017-11-21","cited_by_count":2293},{"id":"2102.04306","title":"TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation","created":"2021-02-08","cited_by_count":1558},{"id":"2105.01601","title":"MLP-Mixer: An all-MLP Architecture for Vision","created":"2021-05-04","cited_by_count":1446},{"id":"1804.03999","title":"Attention U-Net: Learning Where to Look for the Pancreas","created":"2018-04-11","cited_by_count":1435},{"id":"2105.05537","title":"Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation","created":"2021-05-12","cited_by_count":1222},{"id":"2401.09417","title":"Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model","created":"2024-01-17","cited_by_count":1056},{"id":"2401.10166","title":"VMamba: Visual State Space Model","created":"2024-01-18","cited_by_count":969},{"id":"1805.08318","title":"Self-Attention Generative Adversarial Networks","created":"2018-05-21","cited_by_count":809},{"id":"2107.02314","title":"The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification","created":"2021-07-05","cited_by_count":518},{"id":"2103.03024","title":"CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation","created":"2021-03-04","cited_by_count":227},{"id":"2207.08208","title":"Unsupervised Medical Image Translation with Adversarial Diffusion Models","created":"2022-07-17","cited_by_count":192},{"id":"2106.16031","title":"ResViT: Residual vision transformers for multi-modal medical image synthesis","created":"2021-06-30","cited_by_count":177},{"id":"1806.06397","title":"MedGAN: Medical Image Translation using GANs","created":"2018-06-17","cited_by_count":152},{"id":"1802.01221","title":"Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networks","created":"2018-02-05","cited_by_count":132},{"id":"2207.05876","title":"Adaptive Diffusion Priors for Accelerated MRI Reconstruction","created":"2022-07-12","cited_by_count":118},{"id":"1904.12200","title":"Missing MRI Pulse Sequence Synthesis using Multi-Modal Generative Adversarial Network","created":"2019-04-27","cited_by_count":98},{"id":"1708.01155","title":"Deep MR to CT Synthesis using Unpaired Data","created":"2017-08-03","cited_by_count":86},{"id":"2002.05000","title":"Hi-Net: Hybrid-fusion Network for Multi-modal MR Image Synthesis","created":"2020-02-11","cited_by_count":86},{"id":"2103.05940","title":"TransMed: Transformers Advance Multi-modal Medical Image Classification","created":"2021-03-10","cited_by_count":86},{"id":"2105.08059","title":"Unsupervised MRI Reconstruction via Zero-Shot Learned Adversarial Transformers","created":"2021-05-15","cited_by_count":77},{"id":"2307.15208","title":"Generative AI for Medical Imaging: extending the MONAI Framework","created":"2023-07-27","cited_by_count":68},{"id":"2402.19043","title":"WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis","created":"2024-02-29","cited_by_count":56},{"id":"2405.04404","title":"Vision Mamba: A Comprehensive Survey and Taxonomy","created":"2024-05-07","cited_by_count":54},{"id":"2404.18861","title":"Visual Mamba: A Survey and New Outlooks","created":"2024-04-29","cited_by_count":41},{"id":"2204.13738","title":"One Model to Synthesize Them All: Multi-contrast Multi-scale Transformer for Missing Data Imputation","created":"2022-04-28","cited_by_count":40},{"id":"2306.16654","title":"Self-Supervised MRI Reconstruction with Unrolled Diffusion Models","created":"2023-06-29","cited_by_count":38},{"id":"1904.12894","title":"DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis","created":"2019-04-29","cited_by_count":36},{"id":"2103.00634","title":"TransCT: Dual-path Transformer for Low Dose Computed Tomography","created":"2021-02-28","cited_by_count":35},{"id":"1909.11504","title":"mustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesis","created":"2019-09-25","cited_by_count":34},{"id":"1705.02596","title":"Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding","created":"2017-05-07","cited_by_count":33},{"id":"1901.09764","title":"CollaGAN : Collaborative GAN for Missing Image Data Imputation","created":"2019-01-28","cited_by_count":33},{"id":"2202.04175","title":"Federated Learning of Generative Image Priors for MRI Reconstruction","created":"2022-02-08","cited_by_count":33},{"id":"1805.10790","title":"Deep CT to MR Synthesis using Paired and Unpaired Data","created":"2018-05-28","cited_by_count":31},{"id":"1809.04536","title":"Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN","created":"2018-09-12","cited_by_count":31},{"id":"1712.07695","title":"Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth","created":"2017-12-20","cited_by_count":30},{"id":"2104.06757","title":"VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers","created":"2021-04-14","cited_by_count":28},{"id":"2405.06789","title":"Self-Consistent Recursive Diffusion Bridge for Medical Image Translation","created":"2024-05-10","cited_by_count":26},{"id":"2205.11578","title":"BolT: Fused Window Transformers for fMRI Time Series Analysis","created":"2022-05-23","cited_by_count":23},{"id":"2207.06509","title":"One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis","created":"2022-07-13","cited_by_count":22},{"id":"1805.03144","title":"High-resolution medical image synthesis using progressively grown generative adversarial networks","created":"2018-05-08","cited_by_count":17},{"id":"2008.04393","title":"GANBERT: Generative Adversarial Networks with Bidirectional Encoder Representations from Transformers for MRI to PET synthesis","created":"2020-08-10","cited_by_count":15},{"id":"2307.09547","title":"DreaMR: Diffusion-driven Counterfactual Explanation for Functional MRI","created":"2023-07-18","cited_by_count":14},{"id":"2308.01096","title":"Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction","created":"2023-08-02","cited_by_count":14},{"id":"2212.01108","title":"Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis","created":"2022-12-02","cited_by_count":13},{"id":"2105.13993","title":"PTNet: A High-Resolution Infant MRI Synthesizer Based on Transformer","created":"2021-05-28","cited_by_count":11},{"id":"2105.09999","title":"Convolutional Block Design for Learned Fractional Downsampling","created":"2021-05-20","cited_by_count":3}],"next_cursor":null}