IEEE

AVNPSO: Hyperparameter Optimization of Encoder-Decoder Networks for Image Segmentation

Abstract: Image segmentation is crucial in many fields, but existing image segmentation models based on encoder-decoder networks are constrained by manual parameter tuning and the limited ...
Scientific Research Publishing

Xie, E., Wang, W., Yu, Z., et al. (2021) SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers. 35th Conference on Neural Information Processing ...

ABSTRACT: To address the challenges of morphological irregularity and boundary ambiguity in colorectal polyp image segmentation, we propose a Dual-Decoder Pyramid Vision Transformer Network (DDPVT-Net ...
Scientific Research Publishing

Research on Automated Accurate Segmentation Algorithm of Double Kidney in Renal Dynamic Imaging Based on Improved UNet ()

1 School of Electronic Information, Xijing University, Xi’an, China. 2 Department of Nuclear Medicine, Shaanxi Provincial Cancer Hospital, Xi’an, China. 3 Shaanxi University of Chinese Medicine, ...
Frontiers

Deep learning-based automated segmentation for the quantitative diagnosis of cerebral small vessel disease via multisequence MRI

Objective: Existing visual scoring systems for cerebral small vessel disease (CSVD) cannot assess the global lesion load accurately and quantitatively. We aimed to develop an automated segmentation ...
Frontiers

BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...
EurekAlert!

Medical image segmentation using multi-head self-attention-based residual double u-net

The MHSAttResDU-Net incorporates RCC for complexity control and improved generalization under varying lighting. The SSRP unit in encoder-decoder blocks reduces feature map dimensions, capturing key ...