Search Results for author: Fenghe Tang

Found 9 papers, 7 papers with code

Inspecting Model Fairness in Ultrasound Segmentation Tasks

no code implementations5 Dec 2023 Zikang Xu, Fenghe Tang, Quan Quan, Jianrui Ding, Chunping Ning, S. Kevin Zhou

With the rapid expansion of machine learning and deep learning (DL), researchers are increasingly employing learning-based algorithms to alleviate diagnostic challenges across diverse medical tasks and applications.

Fairness Segmentation

SRSNetwork: Siamese Reconstruction-Segmentation Networks based on Dynamic-Parameter Convolution

1 code implementation4 Dec 2023 Bingkun Nian, Fenghe Tang, Jianrui Ding, Pingping Zhang, Jie Yang, S. Kevin Zhou, Wei Liu

In this paper, we present a high-performance deep neural network for weak target image segmentation, including medical image segmentation and infrared image segmentation.

Image Segmentation Medical Image Segmentation +2

MobileUtr: Revisiting the relationship between light-weight CNN and Transformer for efficient medical image segmentation

1 code implementation4 Dec 2023 Fenghe Tang, Bingkun Nian, Jianrui Ding, Quan Quan, Jie Yang, Wei Liu, S. Kevin Zhou

This work revisits the relationship between CNNs and Transformers in lightweight universal networks for medical image segmentation, aiming to integrate the advantages of both worlds at the infrastructure design level.

Image Segmentation Inductive Bias +3

Slide-SAM: Medical SAM Meets Sliding Window

1 code implementation16 Nov 2023 Quan Quan, Fenghe Tang, Zikang Xu, Heqin Zhu, S. Kevin Zhou

To address these problems, we propose Slide-SAM, which treats a stack of three adjacent slices as a prediction window.

Anatomy Image Segmentation +3

CMUNeXt: An Efficient Medical Image Segmentation Network based on Large Kernel and Skip Fusion

2 code implementations2 Aug 2023 Fenghe Tang, Jianrui Ding, Lingtao Wang, Chunping Ning, S. Kevin Zhou

In order to extract global context information while taking advantage of the inductive bias, we propose CMUNeXt, an efficient fully convolutional lightweight medical image segmentation network, which enables fast and accurate auxiliary diagnosis in real scene scenarios.

Image Segmentation Inductive Bias +3

Multi-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Model

1 code implementation16 May 2023 Fenghe Tang, Jianrui Ding, Lingtao Wang, Min Xian, Chunping Ning

Our approach enables the effective transfer of probability distribution knowledge to the segmentation network, resulting in improved segmentation accuracy.

Image Segmentation Medical Image Segmentation +2

CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network

2 code implementations24 Oct 2022 Fenghe Tang, Lingtao Wang, Chunping Ning, Min Xian, Jianrui Ding

However, due to the inherent local characteristics of ordinary convolution operations, U-Net encoder cannot effectively extract global context information.

Image Segmentation Medical Image Segmentation +2

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