10 citations · 14 across the 5 of their papers we have counts for
8 papers
Vision And Text Transformer For Predicting Answerability On Visual Question Answering
Tung Le, Huy Tien Nguyen, Le Minh Nguyen
Answerability on Visual Question Answering is a novel and attractive task to predict answerable scores between images and questions in multi-modal data. Existing works often utiliz…
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…
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…
Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks
Thanh T. Tran, Hieu H. Pham, Thang V. Nguyen +3
Chest radiograph (CXR) interpretation in pediatric patients is error-prone and requires a high level of understanding of radiologic expertise. Recently, deep convolutional neural n…
VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays
Hoang C. Nguyen, Tung T. Le, Hieu H. Pham +1
We introduce a new benchmark dataset, namely VinDr-RibCXR, for automatic segmentation and labeling of individual ribs from chest X-ray (CXR) scans. The VinDr-RibCXR contains 245 CX…
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network
Hieu T. Nguyen, Tung T. Le, Thang V. Nguyen +1
Brain tumor segmentation plays an essential role in medical image analysis. In recent studies, deep convolution neural networks (DCNNs) are extremely powerful to tackle tumor segme…
Interpreting Chest X-rays via CNNs that Exploit Hierarchical Disease Dependencies and Uncertainty Labels
Hieu H. Pham, Tung T. Le, Dat T. Ngo +2
The chest X-rays (CXRs) is one of the views most commonly ordered by radiologists (NHS),which is critical for diagnosis of many different thoracic diseases. Accurately detecting th…
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels
Hieu H. Pham, Tung T. Le, Dat Q. Tran +2
Chest radiography is one of the most common types of diagnostic radiology exams, which is critical for screening and diagnosis of many different thoracic diseases. Specialized algo…