5 papers
Simple is what you need for efficient and accurate medical image segmentation
Xiang Yu, Yayan Chen, Guannan He +12
While modern segmentation models often prioritize performance over practicality, we advocate a design philosophy prioritizing simplicity and efficiency, and attempted high performa…
MS-UMamba: An Improved Vision Mamba Unet for Fetal Abdominal Medical Image Segmentation
Caixu Xu, Junming Wei, Huizhen Chen +4
Recently, Mamba-based methods have become popular in medical image segmentation due to their lightweight design and long-range dependency modeling capabilities. However, current se…
FAMSeg: Fetal Femur and Cranial Ultrasound Segmentation Using Feature-Aware Attention and Mamba Enhancement
Jie He, Minglang Chen, Minying Lu +5
Accurate ultrasound image segmentation is a prerequisite for precise biometrics and accurate assessment. Relying on manual delineation introduces significant errors and is time-con…
DCD: A Semantic Segmentation Model for Fetal Ultrasound Four-Chamber View
Donglian Li, Hui Guo, Minglang Chen +5
Accurate segmentation of anatomical structures in the apical four-chamber (A4C) view of fetal echocardiography is essential for early diagnosis and prenatal evaluation of congenita…
FPDANet: A Multi-Section Classification Model for Intelligent Screening of Fetal Ultrasound
Minglang Chen, Jie He, Caixu Xu +4
ResNet has been widely used in image classification tasks due to its ability to model the residual dependence of constant mappings for linear computation. However, the ResNet metho…