Diffusion model在其他领域中的相关论文

Survey

· [arXiv 2022] Visual Attention Methods in Deep Learning: An In-Depth Survey [pdf]

· [arXiv 2022] Vision+X: A Survey on Multimodal Learning in the Light of Data [pdf]

· [arXiv 2023] Vision Language Models for Vision Tasks: A Survey [pdf]

Medical Report Generation

• [arXiv 2023] Automatic Radiology Report Generation by Learning with Increasingly Hard Negatives [pdf]
• [arXiv 2023] S4M: Generating Radiology Reports by A Single Model for Multiple Body Parts [pdf]
• [arXiv 2023] XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models [pdf]
• [ACL W 2023] shs-nlp at RadSum23: Domain-Adaptive Pre-training of Instruction-tuned LLMs for Radiology Report Impression Generation [pdf]
• [arXiv 2023] Customizing General-Purpose Foundation Models for Medical Report Generation [pdf]
• [CVPR 2023] KiUT: Knowledge-injected U-Transformer for Radiology Report Generation [pdf]
• [arXiv 2023] Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports [pdf]
• [ACL 2023] Replace and Report: NLP Assisted Radiology Report Generation [pdf]
• [ICCV 2023] PRIOR: Prototype Representation Joint Learning from Medical Images and Reports [pdf]
• [ICML W 2023] Rethinking Medical Report Generation: Disease Revealing Enhancement with Knowledge Graph [pdf]
• [MICCAI 2023] Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reporting [pdf]
• [arXiv 2023] IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer [pdf]
• [arXiv 2023] Can Prompt Learning Benefit Radiology Report Generation? [pdf]
• [arXiv 2023] Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting [pdf]
• [arXiv 2023] PromptMRG: Diagnosis-Driven Prompts for Medical Report Generation [pdf]
• [arXiv 2023] Dynamic Multi-Domain Knowledge Networks for Chest X-ray Report Generation [pdf]
• [arXiv 2023] ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Report Generation Based on Multi-institution and Multi-system Data [pdf]
• [MedIA 2023] C^2M-DoT: Cross-modal consistent multi-view medical report generation with domain transfer network [pdf]
• [EMNLP 2023 Findings] Controllable Chest X-Ray Report Generation from Longitudinal Representations [pdf]
• [CVPR 2023] KiUT: Knowledge-Injected U-Transformer for Radiology Report Generation [pdf]
• [CVPR 2023] Interactive and Explainable Region-guided Radiology Report Generation [pdf]
• [MIDL 2023] Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation [pdf]
• [arXiv 2023] Visual-Linguistic Causal Intervention for Radiology Report Generation [pdf]
• [MIDL 2023] Vision-Language Modelling For Radiological Imaging and Reports In The Low Data Regime [pdf]
• [ICASSP 2023] MvCo-DoT:Multi-View Contrastive Domain Transfer Network for Medical Report Generation [pdf]
• [CHIL 2023] Token Imbalance Adaptation for Radiology Report Generation [pdf]
• [arXiv 2023] Boosting Radiology Report Generation by Infusing Comparison Prior [pdf]
• [AAAI 2023] "Nothing Abnormal": Disambiguating Medical Reports via Contrastive Knowledge Infusion [pdf]

Medical Visual Question Answering

• [ISBI 2023] Self-supervised vision-language pretraining for Medical visual question answering [pdf]
• [arXiv 2022] UnICLAM:Contrastive Representation Learning with Adversarial Masking for Unified and Interpretable Medical Vision Question Answering [pdf]
• [arXiv 2023] Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learning [pdf]
• [arXiv 2023] Medical visual question answering using joint self-supervised learning [pdf]
• [ACM MM 2023] RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-training [pdf]
• [IPMI 2023] Q2ATransformer: Improving Medical VQA via an Answer Querying Decoder [pdf]
• [MICCAI 2023] Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Models [pdf]
• [arXiv 2023] PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering [pdf]
• [MICCAI 2023] Masked Vision and Language Pre-training with Unimodal and Multimodal Contrastive Losses for Medical Visual Question Answering [pdf]
• [MICCAI 2023] Localized Questions in Medical Visual Question Answering [pdf]
• [arXiv 2023] Multimodal Prompt Retrieval for Generative Visual Question Answering [pdf]
• [KDD 2023] Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering [pdf]
• [MICCAI 2023] Revisiting Distillation for Continual Learning on Visual Question Localized-Answering in Robotic Surgery [pdf]
• [MICCAI 2023] CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery [pdf]
• [CLEF 2023] UIT-Saviors at MEDVQA-GI 2023: Improving Multimodal Learning with Image Enhancement for Gastrointestinal Visual Question Answering [pdf]
• [DICTA 2023] Visual Question Answering in the Medical Domain [pdf]

Medical Vision-Language Model

• [ICLR 2023] Advancing Radiograph Representation Learning with Masked Record Modeling [pdf]
• [arXiv 2023] ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of Pneumothorax [pdf]
• [MICCAI 2023] PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents [pdf]
• [arXiv 2023] ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Models [pdf]
• [ICCV 2023] MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training [pdf][project]
• [MICCAI 2022] RepsNet: Combining Vision with Language for Automated Medical Reports [pdf]
• [CVPR 2023] Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing [pdf]
• [NeurIPS 2022] Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning [pdf]
• [CVPR W 2023] One-shot and Partially-Supervised Cell Image Segmentation Using Small Visual Prompt [pdf]
• [arXiv 2023] CLIP-Lung: Textual Knowledge-Guided Lung Nodule Malignancy Prediction [pdf]
• [MICCAI 2023] UniSeg: A Prompt-driven Universal Segmentation Model as well as A Strong Representation Learner [pdf]
• [ICCV 2023] UniverSeg: Universal Medical Image Segmentation [pdf]
• [arXiv 2023] Bi-VLGM : Bi-Level Class-Severity-Aware Vision-Language Graph Matching for Text Guided Medical Image Segmentation [pdf]
• [arXiv 2023] Prompt-based Tuning of Transformer Models for Multi-Center Medical Image Segmentation [pdf]
• [arXiv 2023] FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition [pdf]
• [arXiv 2023] ChatCAD+: Towards a Universal and Reliable Interactive CAD using LLMs [pdf]
• [arXiv 2023] XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models [pdf]
• [CHIL 2023] Multi-modal Pre-training for Medical Vision-language Understanding and Generation: An Empirical Study with A New Benchmark [pdf]
• [arXiv 2023] Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias [pdf]
• [arXiv 2023] OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and Dialogue [pdf]
• [ICML W 2023] A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis [pdf]
• [MICCAI 2023] M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization [pdf]
• [MICCAI 2023] Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training [pdf]
• [MICCAI 2023] Unified Medical Image-Text-Label Contrastive Learning With Continuous Prompt [pdf]
• [arXiv 2023] Few-shot medical image classification with simple shape and texture text descriptors using vision-language models [pdf]
• [arXiv 2023] Med-Flamingo: a Multimodal Medical Few-shot Learner [pdf]
• [MICCAI 2023] Ariadne's Thread: Using Text Prompts to Improve Segmentation of Infected Areas from Chest X-ray images [pdf]
• [arXiv 2023] A Foundation LAnguage-Image model of the Retina (FLAIR): Encoding expert knowledge in text supervision [pdf]
• [arXiv 2023] Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Models [pdf]
• [arXiv 2023] Few-shot medical image classification with simple shape and texture text descriptors using vision-language models [pdf]
• [ICCV 2023] ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data [pdf]
• [arXiv 2023] IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-training [pdf]
• [arXiv 2023] Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images [pdf]学术问题付费咨询及相关探讨
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  《中国电机工程学报》优秀审稿专家，《控制与决策》，《系统工程与电子技术》等EI期刊审稿专家，担任《计算机科学》，《电子器件》 ， 《现代制造过程》 ，《船舶工程》 ，《轴承》 ，《工矿自动化》 ，《重庆理工大学学报》 ，《噪声与振动控制》 ，《机械传动》 ，《机械强度》 ，《机械科学与技术》 ，《机床与液压》，《声学技术》，《应用声学》，《石油机械》，《西安工业大学学报》等中文核心审稿专家。
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