125 citations · 174 across the 7 of their papers we have counts for
7 papers
UNGT: Ultrasound Nasogastric Tube Dataset for Medical Image Analysis
Zhaoshan Liu, Chau Hung Lee, Qiujie Lv +2
We develop a novel ultrasound nasogastric tube (UNGT) dataset to address the lack of public nasogastric tube datasets. The UNGT dataset includes 493 images gathered from 110 patien…
Lightweight equivariant model for efficient machine learning interatomic potentials
Ziduo Yang, Xian Wang, Yifan Li +3
In modern computational materials science, deep learning has shown the capability to predict interatomic potentials, thereby supporting and accelerating conventional simulations. H…
MedAugment: Universal Automatic Data Augmentation Plug-in for Medical Image Analysis
Zhaoshan Liu, Qiujie Lv, Yifan Li +2
Data augmentation (DA) has been widely leveraged in computer vision to alleviate data shortage, while its application in medical imaging faces multiple challenges. The prevalent DA…
CECT: Controllable Ensemble CNN and Transformer for COVID-19 Image Classification
Zhaoshan Liu, Lei Shen
The COVID-19 pandemic has resulted in hundreds of million cases and numerous deaths worldwide. Here, we develop a novel classification network CECT by controllable ensemble convolu…
Recent Progress in Transformer-based Medical Image Analysis
Zhaoshan Liu, Qiujie Lv, Ziduo Yang +3
The transformer is primarily used in the field of natural language processing. Recently, it has been adopted and shows promise in the computer vision (CV) field. Medical image anal…
GSDA: Generative Adversarial Network-based Semi-Supervised Data Augmentation for Ultrasound Image Classification
Zhaoshan Liu, Qiujie Lv, Chau Hung Lee +1
Medical Ultrasound (US) is one of the most widely used imaging modalities in clinical practice, but its usage presents unique challenges such as variable imaging quality. Deep Lear…
Deep Co-supervision and Attention Fusion Strategy for Automatic COVID-19 Lung Infection Segmentation on CT Images
Haigen Hu, Leizhao Shen, Qiu Guan +3
Due to the irregular shapes,various sizes and indistinguishable boundaries between the normal and infected tissues, it is still a challenging task to accurately segment the infecte…