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MICCAI2023-Paper-List
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Arxiv 上预发表的 MICCAI 2023 主会中稿论文
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# MICCAI-2023-paper-list 持续更新中... springer 的官网已经放出合订本了，有资源的朋友们可以自行去下载了。需要的直接[联系我的邮箱](mailto:chenluda01@gmail.com)。 注意：如果您获得了任何论文或材料，请确保它们仅用于个人研究和学习目的，并不得用于任何商业目的。 [Part I: Machine learning with limited supervision and machine learning – transfer learning](https://link.springer.com/book/10.1007/978-3-031-43907-0) [Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty](https://link.springer.com/book/10.1007/978-3-031-43895-0) [Part III: Machine learning – explainability, bias and uncertainty; image segmentation](https://link.springer.com/book/10.1007/978-3-031-43898-1) [Part IV: Image segmentation](https://link.springer.com/book/10.1007/978-3-031-43901-8) [Part V: Computer-aided diagnosis](https://link.springer.com/book/10.1007/978-3-031-43904-9) [Part VI: Computer-aided diagnosis; computational pathology](https://link.springer.com/book/10.1007/978-3-031-43987-2) [Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular](https://link.springer.com/book/10.1007/978-3-031-43990-2) [Part VIII: Clinical applications – neuroimaging; microscopy](https://link.springer.com/book/10.1007/978-3-031-43993-3) [Part IX: Image-guided intervention, surgical planning, and data science](https://link.springer.com/book/10.1007/978-3-031-43996-4) [Part X: Image reconstruction and image registration](https://link.springer.com/book/10.1007/978-3-031-43999-5) --- + Dual Conditioned Diffusion Models for Out-Of-Distribution Detection: Application to Fetal Ultrasound Videos (用于分布外检测的双条件扩散模型：胎儿超声视频应用) [[arxiv](https://arxiv.org/abs/2311.00469)] [code] + Rethinking Semi-Supervised Federated Learning: How to co-train fully-labeled and fully-unlabeled client imaging data (反思半监督联合学习：如何共同训练完全标记和完全未标记的客户成像数据) [[arxiv](https://arxiv.org/abs/2310.18815)] [code] + TabAttention: Learning Attention Conditionally on Tabular Data (TabAttention：根据表格数据有条件地学习注意力) [[arxiv](https://arxiv.org/abs/2310.18129)] [[code](https://github.com/SanoScience/Tab-Attentions)] + Interpretable Medical Image Classification using Prototype Learning and Privileged Information (利用原型学习和特权信息进行可解释医学图像分类) [[arxiv](https://arxiv.org/abs/2310.15741)] [[code](https://github.com/XRad-Ulm/Proto-Caps)] + Diffusion-based Data Augmentation for Nuclei Image Segmentation (基于扩散的核图像分割数据增强技术) [[arxiv](https://arxiv.org/abs/2310.14197)] [[code](https://github.com/lhaof/Nudiff)] + Prompt-based Grouping Transformer for Nucleus Detection and Classification (基于提示的核检测与分类分组 Transformer) [[arxiv](https://arxiv.org/abs/2310.14176)] [[code](https://github.com/lhaof/PGT)] + ASC: Appearance and Structure Consistency for Unsupervised Domain Adaptation in Fetal Brain MRI Segmentation (ASC： 胎儿脑磁共振成像分割中无监督领域适应的外观和结构一致性) [[arxiv](https://arxiv.org/abs/2310.14172)] [[code](https://github.com/lhaof/ASC)] + Visual-Attribute Prompt Learning for Progressive Mild Cognitive Impairment Prediction (用于渐进性轻度认知障碍预测的视觉属性提示学习) [[arxiv](https://arxiv.org/abs/2310.14158)] [[code](https://github.com/lhaof/VAPL)] + CXR-CLIP: Toward Large Scale Chest X-ray Language-Image Pre-training (CXR-CLIP：实现大规模胸部 X 射线语言图像预培训) [[arxiv](https://arxiv.org/abs/2310.13292)] [code] + Co-Learning Semantic-aware Unsupervised Segmentation for Pathological Image Registration (用于病理图像配准的协同学习语义感知无监督分割技术) [[arxiv](https://arxiv.org/abs/2310.11040)] [code] + Foundation Ark: Accruing and Reusing Knowledge for Superior and Robust Performance (基础方舟：积累和重用知识，实现卓越稳健的绩效) [[arxiv](https://arxiv.org/abs/2310.09507)] [[code](https://github.com/JLiangLab/Ark)] + Structure-Preserving Instance Segmentation via Skeleton-Aware Distance Transform (通过骨架感知距离变换实现结构保持型实例分割) [[arxiv](https://arxiv.org/abs/2310.05262)] [code] + Machine Learning for Automated Mitral Regurgitation Detection from Cardiac Imaging (从心脏成像中自动检测二尖瓣反流的机器学习) [[arxiv](https://arxiv.org/abs/2310.04871)] [code] + HartleyMHA: Self-Attention in Frequency Domain for Resolution-Robust and Parameter-Efficient 3D Image Segmentation (HartleyMHA：在频域中自我关注，实现分辨率稳定、参数高效的三维图像分割) [[arxiv](https://arxiv.org/abs/2310.04466)] [[code](https://github.com/IBM/multimodal-3d-image-segmentation)] + SMRD: SURE-based Robust MRI Reconstruction with Diffusion Models (SMRD：基于 SURE 的鲁棒 MRI 重构与扩散模型) [[arxiv](https://arxiv.org/abs/2310.01799)] [[code](https://github.com/batuozt/SMRD)] + Learning Expected Appearances for Intraoperative Registration during Neurosurgery (学习神经外科术中登记的预期外观) [[arxiv](https://arxiv.org/abs/2310.01735)] [code] + Cross-adversarial local distribution regularization for semi-supervised medical image segmentation (可学习的跨模态知识提炼，用于缺失模态的多模态学习) [[arxiv](https://arxiv.org/abs/2310.01176)] [[code](https://github.com/PotatoThanh/Cross-adversarial-local-distribution-regularization)] + Learnable Cross-modal Knowledge Distillation for Multi-modal Learning with Missing Modality (可学习的跨模态知识提炼，用于缺失模态的多模态学习) [[arxiv](https://arxiv.org/abs/2310.01035)] [code] + LSOR: Longitudinally-Consistent Self-Organized Representation Learning (LSOR： 纵向一致的自组织表象学习) [[arxiv](https://arxiv.org/abs/2310.00213)] [[code](https://github.com/ouyangjiahong/longitudinal-som-single-modality)] + Towards Novel Class Discovery: A Study in Novel Skin Lesions Clustering (走向新类别发现：新型皮肤病变聚类研究) [[arxiv](https://arxiv.org/abs/2309.16451)] [code] + Automated CT Lung Cancer Screening Workflow using 3D Camera (使用 3D 相机的 CT 肺癌自动筛查工作流程) [[arxiv](https://arxiv.org/abs/2309.15750)] [code] + Speech Audio Synthesis from Tagged MRI and Non-Negative Matrix Factorization via Plastic Transformer (通过 Plastic Transformer 从标记磁共振成像和非负矩阵因式分解合成语音音频) [[arxiv](https://arxiv.org/abs/2309.14586)] [code] + GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation (GL-Fusion：用于多视角超声心动图视频分割的全局-局部融合网络) [[arxiv](https://arxiv.org/abs/2309.11144)] [[code](https://github.com/xmed-lab/GL-Fusion)] + Privacy-preserving Early Detection of Epileptic Seizures in Videos (视频中癫痫发作的隐私保护早期检测) [[arxiv](https://arxiv.org/abs/2309.08794)] [[code](https://github.com/DevD1092/seizure-detection)] + Unified Brain MR-Ultrasound Synthesis using Multi-Modal Hierarchical Representations (利用多模态分层表示进行统一的脑磁共振超声合成) [[arxiv](https://arxiv.org/abs/2309.08747)] [[code](https://github.com/ReubenDo/MHVAE)] + Performance Metrics for Probabilistic Ordinal Classifiers (概率正序分类器的性能指标) [[arxiv](https://arxiv.org/abs/2309.08701)] [code] + ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation (改进医学图像分割的即插即用 CNN 风格转换器) [[arxiv](https://arxiv.org/abs/2309.05674)] [[code](https://github.com/xianlin7/ConvFormer)] + Gall Bladder Cancer Detection from US Images with Only Image Level Labels (基于图像级别标记的超声图像胆囊癌检测) [[arxiv](https://arxiv.org/abs/2309.05261)] [[code](https://gbc-iitd.github.io/wsod-gbc)] + A Spatial-Temporal Deformable Attention based Framework for Breast Lesion Detection in Videos (基于时空变形注意的视频乳腺病变检测框架) [[arxiv](https://arxiv.org/abs/2309.04702)] [[code](https://github.com/AlfredQin/STNet)] + Motion Compensated Unsupervised Deep Learning for 5D MRI (基于运动补偿的 5D MRI 无监督深度学习) [[arxiv](https://arxiv.org/abs/2309.04552)] [code] + Anatomy-informed Data Augmentation for Enhanced Prostate Cancer Detection (增强型前列腺癌的解剖学信息增强技术) [[arxiv](https://arxiv.org/abs/2309.03652)] [[code](https://github.com/MIC-DKFZ/anatomy_informed_DA)] + LightNeuS: Neural Surface Reconstruction in Endoscopy using Illumination Decline (基于光照衰减的内窥镜神经表面重建) [[arxiv](https://arxiv.org/abs/2309.02777)] [code] + Progressive Attention Guidance for Whole Slide Vulvovaginal Candidiasis Screening (全幻灯片念珠菌性外阴阴道炎筛选的渐进式注意指引) [[arxiv](https://arxiv.org/abs/2309.02670)] [[code](https://github.com/caijd2000/MICCAI2023-VVC-Screening)] + Anatomy-Driven Pathology Detection on Chest X-rays (胸部 X 射线解剖驱动的病理学检测) [[arxiv](https://arxiv.org/abs/2309.02578)] [code] + Towards frugal unsupervised detection of subtle abnormalities in medical imaging (医学成像中细微异常的节俭无监督检测) [[arxiv](https://arxiv.org/abs/2309.02458)] [[code](https://github.com/geoffroyO/onlineEM)] + BigFUSE: Global Context-Aware Image Fusion in Dual-View Light-Sheet Fluorescence Microscopy with Image Formation Prior (具有图像形成先验的双视图光片荧光显微镜中的全局上下文感知图像融合) [[arxiv](https://arxiv.org/abs/2309.01865)] [code] + Spectral Adversarial MixUp for Few-Shot Unsupervised Domain Adaptation (少镜头无监督域自适应的谱对抗混合算法) [[arxiv](https://arxiv.org/abs/2309.01207)] [[code](https://github.com/RPIDIAL/SAMix)] + ArSDM: Colonoscopy Images Synthesis with Adaptive Refinement Semantic Diffusion Models (基于自适应细化语义扩散模型的结肠镜图像合成) [[arxiv](https://arxiv.org/abs/2309.01111)] [[code](https://github.com/DuYooho/ArSDM)] + DARC: Distribution-Aware Re-Coloring Model for Generalizable Nucleus Segmentation (可推广核分割的分布感知重着色模型) [[arxiv](https://arxiv.org/abs/2309.00188)] [[code](https://github.com/csccsccsccsc/DARC)] + Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection (克服视觉变换在局部纹理检测中的局限性) [[arxiv](https://arxiv.org/abs/2309.00108)] [[code](https://github.com/mindflow-institue/Laplacian-Former)] + CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and Attention (基于圆查询和注意的全幻灯片图像圆核检测) [[arxiv](https://arxiv.org/abs/2308.16145)] [[code](https://github.com/zhanghx-iim-ahu/CircleFormer)] + Temporal Uncertainty Localization to Enable Human-in-the-loop Analysis of Dynamic Contrast-enhanced Cardiac MRI Datasets (动态增强心脏 MRI 数据的时间不确定性定位) [[arxiv](https://arxiv.org/abs/2308.13488)] [code] + Unsupervised Domain Adaptation for Anatomical Landmark Detection (基于无监督域自适应的解剖标志检测) [[arxiv](https://arxiv.org/abs/2308.13286)] [[code](https://github.com/jhb86253817/UDA_Med_Landmark)] + InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model (基于潜在扩散模型的三维脑 MRI 超分辨率) [[arxiv](https://arxiv.org/abs/2308.12465)] [[code](https://github.com/BioMedAI-UCSC/InverseSR)] + Self-Supervised Learning for Endoscopic Video Analysis (自监督在内窥镜视频分析中的应用) [[arxiv](https://arxiv.org/abs/2308.12394)] [[code](https://github.com/RoyHirsch/endossl)] + PCMC-T1: Free-breathing myocardial T1 mapping with Physically-Constrained Motion Correction (自由呼吸心肌 T1 标测与物理约束运动校正) [[arxiv](https://arxiv.org/abs/2308.11281)] [[code](https://github.com/eyalhana/PCMC-T1)] + Exploring Unsupervised Cell Recognition with Prior Self-activation Maps (基于先验自激活图的无监督细胞识别研究) [[arxiv](https://arxiv.org/abs/2308.11144)] [[code](https://github.com/cpystan/PSM)] + DOMINO++: Domain-aware Loss Regularization for Deep Learning Generalizability (领域感知的深度学习泛化损失正则化) [[arxiv](https://arxiv.org/abs/2308.10453)] [code] + Contrastive Diffusion Model with Auxiliary Guidance for Coarse-to-Fine PET Reconstruction (基于辅助引导的 PET 粗细重建对比扩散模型) [[arxiv](https://arxiv.org/abs/2308.10157)] [[code](https://github.com/Show-han/PET-Reconstruction)] + DMCVR: Morphology-Guided Diffusion Model for 3D Cardiac Volume Reconstruction (形态学引导的三维心脏体积重建扩散模型) [[arxiv](https://arxiv.org/abs/2308.09223)] [[code](https://github.com/hexiaoxiao-cs/DMCVR)] + How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers? (剪枝如何影响长尾多标签医学图像分类器？) [[arxiv](https://arxiv.org/abs/2308.09180)] [[code](https://github.com/VITA-Group/PruneCXR)] + Context-Aware Pseudo-Label Refinement for Source-Free Domain Adaptive Fundus Image Segmentation (基于上下文感知的无源域自适应眼底图像分割伪标签优化) [[arxiv](https://arxiv.org/abs/2308.07731)] [[code](https://github.com/xmed-lab/CPR)] + M&M: Tackling False Positives in Mammography with a Multi-view and Multi-instance Learning Sparse Detector (用多视点多实例学习稀疏检测器处理乳腺摄影中的假阳性) [[arxiv](https://arxiv.org/abs/2308.06420)] [code] + Revolutionizing Space Health (Swin-FSR): Advancing Super-Resolution of Fundus Images for SANS Visual Assessment Technology (提高 SANS 视觉评估技术中眼底图像的超分辨率) [[arxiv](https://arxiv.org/abs/2308.06332)] [code] + A coupled-mechanisms modelling framework for neurodegeneration (神经退行性疾病的耦合机制建模框架) [[arxiv](https://arxiv.org/abs/2308.05536)] [code] + SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation (选择性标签遇到标签有限病变分割的快速调整) [[arxiv](https://arxiv.org/abs/2308.04911)] [code] + An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field (T2 * 胎儿体部 MRI 定量及低场分割的自动化管道) [[arxiv](https://arxiv.org/abs/2308.04903)] [[code](https://github.com/SVRTK/Fetal-T2star-Recon)] + Cross-Dataset Adaptation for Instrument Classification in Cataract Surgery Videos (跨数据集适用于白内障手术视频中的仪器分类) [[arxiv](https://arxiv.org/abs/2308.04035)] [[code](https://github.com/JayParanjape/Barlow-Adaptor)] + Synthetic Augmentation with Large-scale Unconditional Pre-training (大规模无条件预训练的综合增强) [[arxiv](https://arxiv.org/abs/2308.04020)] [[code](https://github.com/karenyyy/HistoDiffAug)] + WarpEM: Dynamic Time Warping for Accurate Catheter Registration in EM-guided Procedures (在电子动态时间规整指导下准确注册导管的方法) [[arxiv](https://arxiv.org/abs/2308.03652)] [code] + Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection (心电图异常检测的多尺度交叉恢复框架) [[arxiv](https://arxiv.org/abs/2308.01639)] [[code](https://github.com/MediaBrain-SJTU/ECGAD)] + Improved Prognostic Prediction of Pancreatic Cancer Using Multi-Phase CT by Integrating Neural Distance and Texture-Aware Transformer (结合神经距离和纹理感知变压器的多相 CT 改进胰腺癌预测) [[arxiv](https://arxiv.org/abs/2308.00507)] [code] + Fundus-Enhanced Disease-Aware Distillation Model for Retinal Disease Classification from OCT Images (基于 OCT 图像的眼底增强疾病感知提取视网膜疾病分类模型) [[arxiv](https://arxiv.org/abs/2308.00291)] [[code](https://github.com/xmed-lab/FDDM)] + Boundary Difference Over Union Loss For Medical Image Segmentation (医疗图像分割联合损失的边界差异) [[arxiv](https://arxiv.org/abs/2308.00220)] [[code](https://github.com/sunfan-bvb/BoundaryDoULoss)] + Domain Adaptation for Medical Image Segmentation using Transformation-Invariant Self-Training (基于转化不变自我训练的医学图像分割领域适应) [[arxiv](https://arxiv.org/abs/2307.16660)] [[code](https://github.com/Negin-Ghamsarian/Transformation-Invariant-Self-Training-MICCAI2023)] + L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space (基于混合曲率空间的蒸馏终身学习) [[arxiv](https://arxiv.org/abs/2307.16459)] [[code](https://github.com/csiro-robotics/L3DMC)] + RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection (一种用于脑肿瘤检测的快速高精度目标检测器) [[arxiv](https://arxiv.org/abs/2307.16412)] [[code](https://github.com/mkang315/RCS-YOLO)] + 3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching between 3D and 2D Networks (基于三维和二维网络交叉教学的稀疏注释三维医学图像分割) [[arxiv](https://arxiv.org/abs/2307.16256)] [[code](https://github.com/HengCai-NJU/3D2DCT)] + Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation (结构保持合成：用于非配对 MR-CT 翻译的 MaskGAN) [[arxiv](https://arxiv.org/abs/2307.16143)] [[code](https://github.com/HieuPhan33/MaskGAN)] + LOTUS: Learning to Optimize Task-based US representations (学习优化基于任务的 US 表示) [[arxiv](https://arxiv.org/abs/2307.16021)] [[code](https://github.com/danivelikova/lotus)] + Scale-aware Test-time Click Adaptation for Pulmonary Nodule and Mass Segmentation (比例感知测试时点击适应肺结节和肿块分割) [[arxiv](https://arxiv.org/abs/2307.15645)] [[code](https://github.com/SplinterLi/SaTTCA)] + vox2vec: A Framework for Self-supervised Contrastive Learning of Voxel-level Representations in Medical Images (医学图像体素级表征的自监督对比学习框架) [[arxiv](https://arxiv.org/abs/2307.14725)] [[code](https://github.com/mishgon/vox2vec)] + Towards multi-modal anatomical landmark detection for ultrasound-guided brain tumor resection with contrastive learning (超声引导脑肿瘤切除对比学习的多模态解剖标志物检测) [[arxiv](https://arxiv.org/abs/2307.14523)] [code] + FocalErrorNet: Uncertainty-aware focal modulation network for inter-modal registration error estimation in ultrasound-guided neurosurgery (超声引导神经外科手术中不确定感知焦点调制网络用于模式间配准误差估计) [[arxiv](https://arxiv.org/abs/2307.14520)] [code] + ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography (内在可解释性和不确定性的动态原型-超声心动图主动脉狭窄分类) [[arxiv](https://arxiv.org/abs/2307.14433)] [[code](https://github.com/hooman007/ProtoASNet)] + Centroid-aware feature recalibration for cancer grading in pathology images (病理图像中肿瘤分级的质心感知特征重校正) [[arxiv](https://arxiv.org/abs/2307.13947)] [[code](https://github.com/colin19950703/CaFeNet)] + Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation (学习以对象为中心的可转移微分同胚变换用于医学图像分割的数据增强) [[arxiv](https://arxiv.org/abs/2307.13645)] [[code](https://github.com/nileshkumar0726/Learning_Transformations)] + An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment (一种可解释的几何加权图形注意网络用于识别与步态损伤相关的功能网络) [[arxiv](https://arxiv.org/abs/2307.13108)] [[code](https://github.com/favour-nerrise/xGW-GAT)] + Multi-View Vertebra Localization and Identification from CT Images (基于 CT 图像的多视点椎体定位与识别) [[arxiv](https://arxiv.org/abs/2307.12845)] [[code](https://github.com/ShanghaiTech-IMPACT/Multi-View-Vertebra-Localization-and-Identification-from-CT-Images)] + Deep Homography Prediction for Endoscopic Camera Motion Imitation Learning (内窥镜摄像机运动仿真学习的深度单应预测) [[arxiv](https://arxiv.org/abs/2307.12792)] [code] + AMAE: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays (适用于胸部 X 线双分布异常检测的预先训练的掩膜自动编码器) [[arxiv](https://arxiv.org/abs/2307.12721)] [code] + SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation (用于 3D 医疗图像分割的带有 Swin 变压器的蒙版多视图) [[arxiv](https://arxiv.org/abs/2307.12591)] [[code](https://github.com/UCSC-VLAA/SwinMM/)] + Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations? (出于错误理由的正确性: 可解释的机器学习技术能够检测出虚假的相关性吗？) [[arxiv](https://arxiv.org/abs/2307.12344)] [[code](https://github.com/ss-sun/right-for-the-wrong-reason)] + EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms (层次图形神经网络在超声心动图左心室标志物检测中的应用) [[arxiv](https://arxiv.org/abs/2307.12229)] [[code](https://github.com/DSL-Lab/echoglad)] + ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising (低剂量 CT 去噪的解剖监督对比学习框架) [[arxiv](https://arxiv.org/abs/2307.12225)] [code] + Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery (再论机器人外科视觉问题本地化回答的持续学习) [[arxiv](https://arxiv.org/abs/2307.12045)] [[code](https://github.com/longbai1006/CS-VQLA)] + SCOL: Supervised Contrastive Ordinal Loss for Abdominal Aortic Calcification Scoring on Vertebral Fracture Assessment Scans (在脊柱骨折评估扫描中监测腹主动脉钙化评分的对比序贯损失) [[arxiv](https://arxiv.org/abs/2307.12006)] [[code](https://github.com/AfsahS/Supervised-Contrastive-Ordinal-Loss-for-Ordinal-Regression)] + COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation (3D 医学图像分割冷启动主动学习的基准) [[arxiv](https://arxiv.org/abs/2307.12004)] [[code](https://github.com/MedICL-VU/COLosSAL)] + Morphology-inspired Unsupervised Gland Segmentation via Selective Semantic Grouping (基于选择性语义分组的形态学启发的无监督腺体分割) [[arxiv](https://arxiv.org/abs/2307.11989)] [[code](https://github.com/xmed-lab/MSSG)] + Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model (基于迭代全局变压器模型的 MRI 任意水平对比剂量仿真) [[arxiv](https://arxiv.org/abs/2307.11980)] [code] + Topology-Preserving Automatic Labeling of Coronary Arteries via Anatomy-aware Connection Classifier (基于拓扑保持的解剖连接分类器的冠状动脉自动标记) [[arxiv](https://arxiv.org/abs/2307.11959)] [[code](https://github.com/zutsusemi/MICCAI2023-TopoLab-Labels/)] + Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction (条件时间注意网络在新生儿皮层表面重建中的应用) [[arxiv](https://arxiv.org/abs/2307.11870)] [[code](https://github.com/m-qiang/CoTAN)] + Deep Reinforcement Learning Based System for Intraoperative Hyperspectral Video Autofocusing (基于深度强化学习的术中高光谱视频自动对焦系统) [[arxiv](https://arxiv.org/abs/2307.11638)] [code] + Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation (一致性指导的自助式半监督医疗图像分割元学习) [[arxiv](https://arxiv.org/abs/2307.11604)] [[code](https://github.com/aijinrjinr/MLB-Seg)] + CortexMorph: fast cortical thickness estimation via diffeomorphic registration using VoxelMorph (基于 VoxelMorph 的差分形态配准快速皮层厚度估计) [[arxiv](https://arxiv.org/abs/2307.11567)] [code] + EndoSurf: Neural Surface Reconstruction of Deformable Tissues with Stereo Endoscope Videos (基于立体内窥镜视频的可变形组织神经表面重建) [[arxiv](https://arxiv.org/abs/2307.11307)] [[code](https://github.com/Ruyi-Zha/endosurf)] + GLSFormer: Gated - Long, Short Sequence Transformer for Step Recognition in Surgical Videos (门控长短序列变压器在外科视频步长识别中的应用) [[arxiv](https://arxiv.org/abs/2307.11081)] [[code](https://github.com/nisargshah1999/GLSFormer)] + Spinal nerve segmentation method and dataset construction in endoscopic surgical scenarios (内窥镜手术中脊神经分割方法及数据集构建) [[arxiv](https://arxiv.org/abs/2307.10955)] [[code](https://github.com/zzzzzzpc/FUnet)] + Soft-tissue Driven Craniomaxillofacial Surgical Planning (软组织驱动的颅颌面外科规划) [[arxiv](https://arxiv.org/abs/2307.10954)] [code] + WeakPolyp: You Only Look Bounding Box for Polyp Segmentation (你只能看到息肉分割的边界框) [[arxiv](https://arxiv.org/abs/2307.10912)] [[code](https://github.com/weijun88/WeakPolyp)] + Parse and Recall: Towards Accurate Lung Nodule Malignancy Prediction like Radiologists (像放射科医生一样准确预测肺结节恶性肿瘤) [[arxiv](https://arxiv.org/abs/2307.10824)] [code] + Community-Aware Transformer for Autism Prediction in fMRI Connectome (fMRI 连接体中用于自闭症预测的社区感知变压器) [[arxiv](https://arxiv.org/abs/2307.10181)] [[code](https://github.com/ubc-tea/Com-BrainTF)] + Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis (利用潜在扩散模型进行跨模态 3D 脑 MRI 合成) [[arxiv](https://arxiv.org/abs/2307.10094)] [code] + Source-Free Domain Adaptive Fundus Image Segmentation with Class-Balanced Mean Teacher (基于类平衡均值教师的无源域自适应眼底图像分割) [[arxiv](https://arxiv.org/abs/2307.09973)] [[code](https://github.com/lloongx/SFDA-CBMT)] + DiffDP: Radiotherapy Dose Prediction via a Diffusion Model (通过扩散模型进行放射治疗剂量预测) [[arxiv](https://arxiv.org/abs/2307.09794)] [code] + Transformer-based Dual-domain Network for Few-view Dedicated Cardiac SPECT Image Reconstructions (基于变压器的双域网络用于少视图专用心脏 SPECT 图像重建) [[arxiv](https://arxiv.org/abs/2307.09624)] [code] + EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation (一种用于皮肤病变分割的高效组增强 UNet) [[arxiv](https://arxiv.org/abs/2307.08473)] [[code](https://github.com/JCruan519/EGE-UNet)] + M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization (基于冻结语言模型和潜在空间几何优化的医学视觉语言预训练) [[arxiv](https://arxiv.org/abs/2307.08347)] [[code](https://github.com/cheliu-computation/M-FLAG-MICCAI2023)] + A Novel Multi-Task Model Imitating Dermatologists for Accurate Differential Diagnosis of Skin Diseases in Clinical Images (一种新的模仿皮肤科医生的多任务模型用于临床图像中皮肤病的精确鉴别诊断) [[arxiv](https://arxiv.org/abs/2307.08308)] [code] + Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network (基于像素病变患者网络的肝脏肿瘤 CT 筛查与诊断) [[arxiv](https://arxiv.org/abs/2307.08268)] [code] + Boundary-weighted logit consistency improves calibration of segmentation networks (边界加权 logit 一致性改进分割网络的校准) [[arxiv](https://arxiv.org/abs/2307.08163)] [code] + MUVF-YOLOX: A Multi-modal Ultrasound Video Fusion Network for Renal Tumor Diagnosis (一种用于肾肿瘤诊断的多模式超声视频融合网络) [[arxiv](https://arxiv.org/abs/2307.07807)] [[code](https://github.com/JeunyuLi/MUAF)] + ConTrack: Contextual Transformer for Device Tracking in X-ray (X 射线设备跟踪的上下文转换器) [[arxiv](https://arxiv.org/abs/2307.07541)] [code] + Frequency Domain Adversarial Training for Robust Volumetric Medical Segmentation (用于鲁棒体积医学分割的频域对抗性训练) [[arxiv](https://arxiv.org/abs/2307.07269)] [[code](https://github.com/asif-hanif/vafa)] + Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training (知识提升：医学对比视觉语言预训练的再思考) [[arxiv](https://arxiv.org/abs/2307.07246)] [[code](https://github.com/ChenXiaoFei-CS/KoBo)] + CellGAN: Conditional Cervical Cell Synthesis for Augmenting Cytopathological Image Classification (用于增强细胞病理图像分类的条件宫颈细胞合成) [[arxiv](https://arxiv.org/abs/2307.06182)] [[code](https://github.com/ZhenrongShen/CellGAN)] + Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal Feature Affinity Learning for Robust Video Segmentation (用序列先验校正噪声标签：用于鲁棒视频分割的多尺度时间特征仿射学习) [[arxiv](https://arxiv.org/abs/2307.05898)] [[code](https://github.com/BeileiCui/MS-TFAL)] + FreeSeed: Frequency-band-aware and Self-guided Network for Sparse-view CT Reconstruction (用于稀疏视图 CT 重建的频带感知和自导网络) [[arxiv](https://arxiv.org/abs/2307.05890)] [[code](https://github.com/Masaaki-75/freeseed)] + Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reporting (一种用于结构化放射学报告的新型 VQA 基准和方法) [[arxiv](https://arxiv.org/abs/2307.05766)] [[code](https://github.com/ChantalMP/Rad-ReStruct)] + DRMC: A Generalist Model with Dynamic Routing for Multi-Center PET Image Synthesis (一种具有动态路由的多中心 PET 图像合成广义模型) [[arxiv](https://arxiv.org/abs/2307.05249)] [[code](https://github.com/Yaziwel/Multi-Center-PET-Image-Synthesis)] + CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery (用于机器人手术中视觉问题本地化回答的共注意门控视觉语言嵌入) [[arxiv](https://arxiv.org/abs/2307.05182)] [[code](https://github.com/longbai1006/CAT-ViL)] + Multimodal brain age estimation using interpretable adaptive population-graph learning (利用可解释的自适应群体图学习进行多模态脑年龄估计) [[arxiv](https://arxiv.org/abs/2307.04639)] [[code](https://github.com/bintsi/adaptive-graph-learning)] + Weakly-supervised positional contrastive learning: application to cirrhosis classification (弱监督位置对比学习在肝硬化分类中的应用) [[arxiv](https://arxiv.org/abs/2307.04617)] [[code](https://github.com/Guerbet-AI/wsp-contrastive)] + Cluster-Induced Mask Transformers for Effective Opportunistic Gastric Cancer Screening on Non-contrast CT Scans (弱监督位置对比学习在肝硬化分类中的应用) [[arxiv](https://arxiv.org/abs/2307.04525)] [code] + CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation (CoactSeg:从异构数据中学习用于新的多发性硬化病变分割) [[arxiv](https://arxiv.org/abs/2307.04513)] [[code](https://github.com/ycwu1997/CoactSeg)] + Partial Vessels Annotation-based Coronary Artery Segmentation with Self-training and Prototype Learning (基于局部血管注释的自训练和原型学习冠状动脉分割) [[arxiv](https://arxiv.org/abs/2307.04472)] [[code](https://github.com/ZhangZ7112/PVA-CAS)] + Towards Generalizable Diabetic Retinopathy Grading in Unseen Domains (在未知领域进行糖尿病视网膜病变分级) [[arxiv](https://arxiv.org/abs/2307.04378)] [[code](https://github.com/chehx/DGDR)] + Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping (基于帧顺序翻转的数据集生成从部分注释中检测有丝分裂) [[arxiv](https://arxiv.org/abs/2307.04113)] [[code](https://github.com/naivete5656/MDPAFOF)] + Ariadne's Thread:Using Text Prompts to Improve Segmentation of Infected Areas from Chest X-ray images (Ariadne 的思路：使用文本提示改进胸部X射线图像中感染区域的分割) [[arxiv](https://arxiv.org/abs/2307.03942)] [[code](https://github.com/Junelin2333/LanGuideMedSeg-MICCAI2023)] + Unsupervised 3D out-of-distribution detection with latent diffusion models (具有潜在扩散模型的无监督三维分布外检测) [[arxiv](https://arxiv.org/abs/2307.03777)] [[code](https://github.com/marksgraham/ddpm-ood)] + Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery (癌症微创手术中腹腔镜探头传感区的检测) [[arxiv](https://arxiv.org/abs/2307.03662)] [[code](https://github.com/br0202/Sensing_area_detection)]
