Name: Ngoc-Thang Bui
Type: User
Company: Biomedical Engineering Department, Pukyong National University
Bio: I am a Ph.D. in biomedical engineering. My research interests include high-speed AD converter for ultrasound imaging system, biomedical signal analysis, HiFU.
Location: Busan, Korea
Blog: https://www.nbmlab.com/members
Ngoc-Thang Bui's Projects
3D Liver Segmentation with GAN
GAN code for generating lung nodule ct scans
Fever screening with IR & RGB cameras and Deep CNNs
Project on an algorithm to read automatically the water consumption with an image of a meter
AIDE: Annotation-efficient deep learning for automatic medical image segmentation
AI projects in python, mostly Jupyter notebooks.
Awesome GAN for Medical Imaging
Bioinformatics with Python Cookbook Second Edition, published by Packt
bioinformatic
Biomedical Image Segmentation via RMSPP-UNet
A toolbox for box-supervised instance segmentation.
ESP32-CAM and Python codes to read digits
Basic UNet, AUNet, and ResNet architecture models and new variations: Connected-UNets, Connected-AUNets, and Connected-ResUNets architecture models
Code release for ConvNeXt model
Data repository of Project Coswara
This Repository consists if works related to the detection of COVID-19 and related disease from Chest Radiographs by using Image Processing Techniques, Computer Vision and Machine Learning methods.
Open benchmark dataset of COVID-19 related ultrasound imaging data, curated and systematically validated — Ensemble de données de référence ouvert d'imagerie échographique liées à la COVID-19, organisé et systématiquement validé
Open source lung ultrasound (LUS) data collection initiative for COVID-19.
A GAN based framework for adding and removing medical evidence in 3D volumetric medical scans
Prediction of Blood Pressure from ECG and PPG signals using regression methods.
[MICCAI2019 & TMI2020] Chest X-ray decomposition with unpaired CT knowledge
Collection of papers, datasets, code and other resources for object tracking and detection using deep learning
ResUNet, a semantic segmentation model inspired by the deep residual learning and UNet. An architecture that take advantages from both(Residual and UNet) models.
Fully automatic brain tumour segmentation using Deep 3-D convolutional neural networks
"DeepDPM: Deep Clustering With An Unknown Number of Clusters" [CVPR 2022]
Deep learning driven structured illumination microscopy
Software drivers for systems without OS