137 citations · 166 across the 6 of their papers we have counts for
6 papers
Inspecting Model Fairness in Ultrasound Segmentation Tasks
Zikang Xu, Fenghe Tang, Quan Quan +3
With the rapid expansion of machine learning and deep learning (DL), researchers are increasingly employing learning-based algorithms to alleviate diagnostic challenges across dive…
CMUNeXt: An Efficient Medical Image Segmentation Network based on Large Kernel and Skip Fusion
Fenghe Tang, Jianrui Ding, Lingtao Wang +2
The U-shaped architecture has emerged as a crucial paradigm in the design of medical image segmentation networks. However, due to the inherent local limitations of convolution, a f…
Thinking Twice: Clinical-Inspired Thyroid Ultrasound Lesion Detection Based on Feature Feedback
Lingtao Wang, Jianrui Ding, Fenghe Tang +1
Accurate detection of thyroid lesions is a critical aspect of computer-aided diagnosis. However, most existing detection methods perform only one feature extraction process and the…
Multi-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Model
Fenghe Tang, Jianrui Ding, Lingtao Wang +2
Medical image segmentation is a critical step in computer-aided diagnosis, and convolutional neural networks are popular segmentation networks nowadays. However, the inherent local…
CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network
Fenghe Tang, Lingtao Wang, Chunping Ning +2
U-Net and its extensions have achieved great success in medical image segmentation. However, due to the inherent local characteristics of ordinary convolution operations, U-Net enc…
BUSIS: A Benchmark for Breast Ultrasound Image Segmentation
Min Xian, Yingtao Zhang, H. D. Cheng +6
Breast ultrasound (BUS) image segmentation is challenging and critical for BUS Comput-er-Aided Diagnosis (CAD) systems. Many BUS segmentation approaches have been studied in the la…