21 citations · 111 across the 28 of their papers we have counts for
7 papers · 1 filter
The pitfalls of using open data to develop deep learning solutions for COVID-19 detection in chest X-rays
Rachael Harkness, Geoff Hall, Alejandro F Frangi +2
Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from chest X-rays. With little to no direct access to hospital data, the AI community…
Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstruction
Mingyuan Luo, Xin Yang, Xiaoqiong Huang +6
3D ultrasound (US) is widely used for its rich diagnostic information. However, it is criticized for its limited field of view. 3D freehand US reconstruction is promising in addres…
Flip Learning: Erase to Segment
Yuhao Huang, Xin Yang, Yuxin Zou +7
Nodule segmentation from breast ultrasound images is challenging yet essential for the diagnosis. Weakly-supervised segmentation (WSS) can help reduce time-consuming and cumbersome…
Style Curriculum Learning for Robust Medical Image Segmentation
Zhendong Liu, Van Manh, Xin Yang +6
The performance of deep segmentation models often degrades due to distribution shifts in image intensities between the training and test data sets. This is particularly pronounced…
A Deep Discontinuity-Preserving Image Registration Network
Xiang Chen, Nishant Ravikumar, Yan Xia +1
Image registration aims to establish spatial correspondence across pairs, or groups of images, and is a cornerstone of medical image computing and computer-assisted-interventions.…
CAR-Net: Unsupervised Co-Attention Guided Registration Network for Joint Registration and Structure Learning
Xiang Chen, Yan Xia, Nishant Ravikumar +1
Image registration is a fundamental building block for various applications in medical image analysis. To better explore the correlation between the fixed and moving images and imp…