151 citations · 198 across the 8 of their papers we have counts for
6 papers · 1 filter
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
Jiawei Yang, Yao Zhang, Yuan Liang +3
Deep learning models are notoriously data-hungry. Thus, there is an urging need for data-efficient techniques in medical image analysis, where well-annotated data are costly and ti…
Exploring Instance-Level Uncertainty for Medical Detection
Jiawei Yang, Yuan Liang, Yao Zhang +3
The ability of deep learning to predict with uncertainty is recognized as key for its adoption in clinical routines. Moreover, performance gain has been enabled by modelling uncert…
Double-Uncertainty Weighted Method for Semi-supervised Learning
Yixin Wang, Yao Zhang, Jiang Tian +4
Though deep learning has achieved advanced performance recently, it remains a challenging task in the field of medical imaging, as obtaining reliable labeled training data is time-…
AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?
Jun Ma, Yao Zhang, Song Gu +14
With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved…
Dermoscopic Image Analysis for ISIC Challenge 2018
Jinyi Zou, Xiao Ma, Cheng Zhong +1
This short paper reports the algorithms we used and the evaluation performances for ISIC Challenge 2018. Our team participates in all the tasks in this challenge. In lesion segment…