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Mengting Liu

2 accepted papers

2024

Rolling-Unet: Revitalizing MLP’s Ability to Efficiently Extract Long-Distance Dependencies for Medical Image Segmentation

AAAI 2024technical

Medical image segmentation methods based on deep learning network are mainly divided into CNN and Transformer. However, CNN struggles to capture long-distance dependencies, while Transformer suffers from high computational complexity and poor local feature learning. To efficiently extract and fuse l…

Cited by 30SourcePDFScholar
2024

SSR-GPCsT: Deep Learning Models Based on Functional Connectivity Maps in Autism Research

ICASSP 2024accepted

Autism is a neurodevelopmental disorder characterized by difficulties in social interaction, communication, and sensory sensitivity. Functional magnetic resonance imaging (fMRI) is a commonly used brain imaging technique to obtain functional connectivity information in individuals with autism. Howev…

Cited by 0SourceScholar