29 citations · 34 across the 4 of their papers we have counts for
4 papers
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…
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography
Hieu T. Nguyen, Ha Q. Nguyen, Hieu H. Pham +4
Mammography, or breast X-ray, is the most widely used imaging modality to detect cancer and other breast diseases. Recent studies have shown that deep learning-based computer-assis…
VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs
Hieu T. Nguyen, Hieu H. Pham, Nghia T. Nguyen +4
Radiographs are used as the most important imaging tool for identifying spine anomalies in clinical practice. The evaluation of spinal bone lesions, however, is a challenging task…
VinDr-CXR: An open dataset of chest X-rays with radiologist's annotations
Ha Q. Nguyen, Khanh Lam, Linh T. Le +21
Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learn…