33 citations · 111 across the 21 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms
Sam B. Tran, Huyen T. X. Nguyen, Chi Phan +2
Image augmentation techniques have been widely investigated to improve the performance of deep learning (DL) algorithms on mammography classification tasks. Recent methods have pro…
A CNN-LSTM Architecture for Detection of Intracranial Hemorrhage on CT scans
Nhan T. Nguyen, Dat Q. Tran, Nghia T. Nguyen +1
We propose a novel method that combines a convolutional neural network (CNN) with a long short-term memory (LSTM) mechanism for accurate prediction of intracranial hemorrhage on co…
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…
Correcting differences in multi-site neuroimaging data using Generative Adversarial Networks
Harrison Nguyen, Richard W. Morris, Anthony W. Harris +2
Magnetic Resonance Imaging (MRI) of the brain has been used to investigate a wide range of neurological disorders, but data acquisition can be expensive, time-consuming, and inconv…