29 citations · 122 across the 33 of their papers we have counts for
35 papers
Is H&E Image-to-Spatial Transcriptomics Simpler Than It Looks?
Duc T. Nguyen, Thanh Ha Do, Phuong M. Cao +1
Predicting spatial gene expression from routine H&E histology offers a scalable route toward spatial molecular profiling. Recent work has pursued increasingly sophisticated archite…
When Oracle Conditioning Misleads Deployment: Conditioning-Availability Bias in Echocardiographic Segmentation
Dang P. M. Cao, Hieu D. Pham, Hieu Pham
Conditional segmentation models may be trained and evaluated with auxiliary signals cleaner than those available at deployment. We study this protocol-level manifestation of shortc…
When Measurement Conventions Masquerade as Calibration Gains in Cardiac Digital Twins
Dang P. M. Cao, Hieu Pham
Cardiac digital twins convert clinical images into physiological measurements through observation operators, yet calibration studies often assume a fixed reference convention. Acro…
Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
Giang Nguyen, Raghav Mehta, Emma A. M. Stanley +4
Foundation models are increasingly used as image feature extractors for mammography, but their robustness under external domain shift remains unclear. We benchmark 15 foundation-mo…
VinDr-CXR-VQA: A Visual Question Answering Dataset for Explainable Chest X-Ray Analysis with Multi-Task Learning
Dang H. Nguyen, Hieu H. Pham, Hao T. Nguyen
We present VinDr-CXR-VQA, a large-scale chest X-ray dataset for explainable Medical Visual Question Answering (Med-VQA) with spatial grounding. The dataset contains 17,597 question…
Learning to Estimate Critical Gait Parameters from Single-View RGB Videos with Transformer-Based Attention Network
Quoc Hung T. Le, Hieu H. Pham
Musculoskeletal diseases and cognitive impairments in patients lead to difficulties in movement as well as negative effects on their psychological health. Clinical gait analysis, a…
MPCNN: A Novel Matrix Profile Approach for CNN-based Sleep Apnea Classification
Hieu X. Nguyen, Duong V. Nguyen, Hieu H. Pham +1
Sleep apnea (SA) is a significant respiratory condition that poses a major global health challenge. Previous studies have investigated several machine and deep learning models for…
TransReg: Cross-transformer as auto-registration module for multi-view mammogram mass detection
Hoang C. Nguyen, Chi Phan, Hieu H. Pham
Screening mammography is the most widely used method for early breast cancer detection, significantly reducing mortality rates. The integration of information from multi-view mammo…
Echocardiography Segmentation Using Neural ODE-based Diffeomorphic Registration Field
Phi Nguyen Van, Hieu Pham Huy, Long Tran Quoc
Convolutional neural networks (CNNs) have recently proven their excellent ability to segment 2D cardiac ultrasound images. However, the majority of attempts to perform full-sequenc…
Multimodal contrastive learning for diagnosing cardiovascular diseases from electrocardiography (ECG) signals and patient metadata
Tue M. Cao, Nhat H. Tran, Phi Le Nguyen +1
This work discusses the use of contrastive learning and deep learning for diagnosing cardiovascular diseases from electrocardiography (ECG) signals. While the ECG signals usually c…
Evaluating the impact of an explainable machine learning system on the interobserver agreement in chest radiograph interpretation
Hieu H. Pham, Ha Q. Nguyen, Hieu T. Nguyen +2
We conducted a prospective study to measure the clinical impact of an explainable machine learning system on interobserver agreement in chest radiograph interpretation. The AI syst…
Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation
Hieu H. Pham, Khiem H. Le, Tuan V. Tran +1
The work discusses the use of machine learning algorithms for anomaly detection in medical image analysis and how the performance of these algorithms depends on the number of annot…
Ensemble Learning of Myocardial Displacements for Myocardial Infarction Detection in Echocardiography
Nguyen Tuan, Phi Nguyen, Dai Tran +10
Early detection and localization of myocardial infarction (MI) can reduce the severity of cardiac damage through timely treatment interventions. In recent years, deep learning tech…
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions
Thuy Dung Nguyen, Tuan Nguyen, Phi Le Nguyen +3
Federated learning (FL) is a machine learning (ML) approach that allows the use of distributed data without compromising personal privacy. However, the heterogeneous distribution o…
Multi-stream Fusion for Class Incremental Learning in Pill Image Classification
Trong-Tung Nguyen, Hieu H. Pham, Phi Le Nguyen +2
Classifying pill categories from real-world images is crucial for various smart healthcare applications. Although existing approaches in image classification might achieve a good p…
Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese
Thao T. B. Nguyen, Tam M. Vo, Thang V. Nguyen +2
We propose a data collecting and annotation pipeline that extracts information from Vietnamese radiology reports to provide accurate labels for chest X-ray (CXR) images. This can b…
Enhancing Deep Learning-based 3-lead ECG Classification with Heartbeat Counting and Demographic Data Integration
Khiem H. Le, Hieu H. Pham, Thao B. T. Nguyen +2
Nowadays, an increasing number of people are being diagnosed with cardiovascular diseases (CVDs), the leading cause of death globally. The gold standard for identifying these heart…
Video-based Human Action Recognition using Deep Learning: A Review
Hieu H. Pham, Louahdi Khoudour, Alain Crouzil +2
Human action recognition is an important application domain in computer vision. Its primary aim is to accurately describe human actions and their interactions from a previously uns…
An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
Hieu H. Pham, Ha Q. Nguyen, Hieu T. Nguyen +2
Recent artificial intelligence (AI) algorithms have achieved radiologist-level performance on various medical classification tasks. However, only a few studies addressed the locali…
Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks
Thao Nguyen, Hieu H. Pham, Huy Khiem Le +3
The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, raising the need to develop novel tools to provide rapid and cost-effective screening and diag…
Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices
Dat T. Ngo, Thao T. B. Nguyen, Hieu T. Nguyen +3
The rapid development in representation learning techniques such as deep neural networks and the availability of large-scale, well-annotated medical imaging datasets have to a rapi…
LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification
Khiem H. Le, Hieu H. Pham, Thao BT. Nguyen +3
Cardiovascular diseases (CVDs) are a group of heart and blood vessel disorders that is one of the most serious dangers to human health, and the number of such patients is still gro…
Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling
Binh T. Dao, Thang V. Nguyen, Hieu H. Pham +1
A fully automated system for interpreting abdominal computed tomography (CT) scans with multiple phases of contrast enhancement requires an accurate classification of the phases. T…
Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis
Khiem H. Le, Tuan V. Tran, Hieu H. Pham +3
Building an accurate computer-aided diagnosis system based on data-driven approaches requires a large amount of high-quality labeled data. In medical imaging analysis, multiple exp…