Thông tin nhà nghiên cứu KH&CN

Frame Permutation Quantization

A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms

VinDr-SpineXR: A large annotated medical image dataset for spinal lesions detection and classification from radiographs

VinDr Lab: A Data Platform for Medical AI

Unveiling prognostics biomarkers of tyrosine metabolism reprogramming in liver cancer by cross-platform gene expression analyses

Generalized Poisson summation formula for tempered distributions

Compression of human body sequences using graph wavelet filter banks

Subspace methods for computational relighting

Deep Learning for Radar Pulse Detection

An image processing approach to wideband spectrum sensing of heterogeneous signals

Deep Q-learning with multiband sensing for dynamic spectrum access

Classification of pulse repetition interval modulations using neural networks

Deep Learning for Pulse Repetition Interval Classification

A CNN-LSTM Architecture for Detection of Intracranial Hemorrhage on CT scans

Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels

VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays

DICOM Imaging Router: An Open Deep Learning Framework for Classification of Body Parts from DICOM X-ray Scans

Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks

VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs

A novel multi-view deep learning approach for BI-RADS and density assessment of mammograms

Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices

Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese

Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling

Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings

An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph

Learning from multiple expert annotators for enhancing anomaly detection in medical Image analysis

VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations

PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children

VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography

Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels

Approximation of Non-decaying Signals from Shift-Invariant Subspaces

CNN-based projected gradient descent for consistent CT image reconstruction

A sampling theory for non-decaying signals

Learning convex regularizers for optimal Bayesian denoising

Downsampling of signals on graphs via maximum spanning trees

Inverse Rendering of Lambertian Surfaces Using Subspace Methods

Concentric permutation source codes

Frame Permutation Quantization

On concentric spherical codes and permutation codes with multiple initial codewords

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