57 citations · 353 across the 50 of their papers we have counts for
16 papers · 1 filter
T3D: Advancing 3D Medical Vision-Language Pre-training by Learning Multi-View Visual Consistency
Che Liu, Cheng Ouyang, Yinda Chen +7
While 3D visual self-supervised learning (vSSL) shows promising results in capturing visual representations, it overlooks the clinical knowledge from radiology reports. Meanwhile,…
G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training
Che Liu, Cheng Ouyang, Sibo Cheng +3
Recently, medical vision-language pre-training (VLP) has reached substantial progress to learn global visual representation from medical images and their paired radiology reports.…
Efficient deep data assimilation with sparse observations and time-varying sensors
Sibo Cheng, Che Liu, Yike Guo +1
Variational Data Assimilation (DA) has been broadly used in engineering problems for field reconstruction and prediction by performing a weighted combination of multiple sources of…
IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-training
Che Liu, Sibo Cheng, Miaojing Shi +3
In the field of medical Vision-Language Pre-training (VLP), significant efforts have been devoted to deriving text and image features from both clinical reports and associated medi…
Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images
Che Liu, Anand Shah, Wenjia Bai +1
Medical Vision-Language Pre-training (VLP) learns representations jointly from medical images and paired radiology reports. It typically requires large-scale paired image-text data…
ETP: Learning Transferable ECG Representations via ECG-Text Pre-training
Che Liu, Zhongwei Wan, Sibo Cheng +2
In the domain of cardiovascular healthcare, the Electrocardiogram (ECG) serves as a critical, non-invasive diagnostic tool. Although recent strides in self-supervised learning (SSL…
A generative model for surrogates of spatial-temporal wildfire nowcasting
Sibo Cheng, Yike Guo, Rossella Arcucci
Recent increase in wildfires worldwide has led to the need for real-time fire nowcasting. Physics-driven models, such as cellular automata and computational fluid dynamics can prov…
M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization
Che Liu, Sibo Cheng, Chen Chen +5
Medical vision-language models enable co-learning and integrating features from medical imaging and clinical text. However, these models are not easy to train and the latent repres…
A novel approach for predicting epidemiological forecasting parameters based on real-time signals and Data Assimilation
Romain Molinas, César Quilodrán Casas, Rossella Arcucci +1
This paper proposes a novel approach to predict epidemiological parameters by integrating new real-time signals from various sources of information, such as novel social media-base…
Generative Text-Guided 3D Vision-Language Pretraining for Unified Medical Image Segmentation
Yinda Chen, Che Liu, Wei Huang +3
Vision-Language Pretraining (VLP) has demonstrated remarkable capabilities in learning visual representations from textual descriptions of images without annotations. Yet, effectiv…
Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias
Zhongwei Wan, Che Liu, Mi Zhang +6
The scarcity of data presents a critical obstacle to the efficacy of medical visionlanguage pre-training (VLP). A potential solution lies in the combination of datasets from variou…
Analyzing drop coalescence in microfluidic device with a deep learning generative model
Kewei Zhu, Sibo Cheng, Nina Kovalchuk +4
Predicting drop coalescence based on process parameters is crucial for experiment design in chemical engineering. However, predictive models can suffer from the lack of training da…
Frozen Language Model Helps ECG Zero-Shot Learning
Jun Li, Che Liu, Sibo Cheng +2
The electrocardiogram (ECG) is one of the most commonly used non-invasive, convenient medical monitoring tools that assist in the clinical diagnosis of heart diseases. Recently, de…
Optimization of microfluidic synthesis of silver nanoparticles: a generic approach using machine learning
Konstantia Nathanael, Sibo Cheng, Nina M. Kovalchuk +2
The properties of silver nanoparticles (AgNPs) are affected by various parameters, making optimisation of their synthesis a laborious task. This optimisation is facilitated in this…
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review
Sibo Cheng, Cesar Quilodran-Casas, Said Ouala +14
Data Assimilation (DA) and Uncertainty quantification (UQ) are extensively used in analysing and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical a…
Spectral Cross-Domain Neural Network with Soft-adaptive Threshold Spectral Enhancement
Che Liu, Sibo Cheng, Weiping Ding +1
Electrocardiography (ECG) signals can be considered as multi-variable time-series. The state-of-the-art ECG data classification approaches, based on either feature engineering or d…