21 citations · 47 across the 12 of their papers we have counts for
12 papers
Suppressing Prior-Comparison Hallucinations in Radiology Report Generation via Semantically Decoupled Latent Steering
Ao Li, Rui Liu, Mingjie Li +6
Automated radiology report generation using vision-language models (VLMs) is limited by the risk of prior-comparison hallucination, where the model generates historical findings un…
Medical Report Generation Is A Multi-label Classification Problem
Yijian Fan, Zhenbang Yang, Rui Liu +2
Medical report generation is a critical task in healthcare that involves the automatic creation of detailed and accurate descriptions from medical images. Traditionally, this task…
Contrastive Learning with Counterfactual Explanations for Radiology Report Generation
Mingjie Li, Haokun Lin, Liang Qiu +4
Due to the common content of anatomy, radiology images with their corresponding reports exhibit high similarity. Such inherent data bias can predispose automatic report generation…
Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection
Junfei Yi, Jianxu Mao, Tengfei Liu +5
Knowledge distillation (KD) is a widely adopted and effective method for compressing models in object detection tasks. Particularly, feature-based distillation methods have shown r…
Predicting Genetic Mutation from Whole Slide Images via Biomedical-Linguistic Knowledge Enhanced Multi-label Classification
Gexin Huang, Chenfei Wu, Mingjie Li +6
Predicting genetic mutations from whole slide images is indispensable for cancer diagnosis. However, existing work training multiple binary classification models faces two challeng…
Mask Propagation for Efficient Video Semantic Segmentation
Yuetian Weng, Mingfei Han, Haoyu He +4
Video Semantic Segmentation (VSS) involves assigning a semantic label to each pixel in a video sequence. Prior work in this field has demonstrated promising results by extending im…
Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining
Bingqian Lin, Zicong Chen, Mingjie Li +13
Medical artificial general intelligence (MAGI) enables one foundation model to solve different medical tasks, which is very practical in the medical domain. It can significantly re…
A Benchmark for Cycling Close Pass Detection from Video Streams
Mingjie Li, Ben Beck, Tharindu Rathnayake +5
Cycling is a healthy and sustainable mode of transport. However, interactions with motor vehicles remain a key barrier to increased cycling participation. The ability to detect pot…
Dynamic Graph Enhanced Contrastive Learning for Chest X-ray Report Generation
Mingjie Li, Bingqian Lin, Zicong Chen +3
Automatic radiology reporting has great clinical potential to relieve radiologists from heavy workloads and improve diagnosis interpretation. Recently, researchers have enhanced da…
Mitigating Data Redundancy to Revitalize Transformer-based Long-Term Time Series Forecasting System
Mingjie Li, Rui Liu, Guangsi Shi +5
Long-term time-series forecasting (LTSF) is fundamental to various real-world applications, where Transformer-based models have become the dominant framework due to their ability t…
Cross-modal Clinical Graph Transformer for Ophthalmic Report Generation
Mingjie Li, Wenjia Cai, Karin Verspoor +3
Automatic generation of ophthalmic reports using data-driven neural networks has great potential in clinical practice. When writing a report, ophthalmologists make inferences with…
Auxiliary Signal-Guided Knowledge Encoder-Decoder for Medical Report Generation
Mingjie Li, Fuyu Wang, Xiaojun Chang +1
Beyond the common difficulties faced in the natural image captioning, medical report generation specifically requires the model to describe a medical image with a fine-grained and…