Mask-embedding and feature-fused network for medical image segmentation
Bibliographic entry
Tang, Yi. Mask-embedding and feature-fused network for medical image segmentation / Yi Tang, Di Zhao, A. Gourinovitch // Беларусь-Китай: контуры инновационно-технологического сотрудничества : сборник материалов научно-практической конференции (Минск, 19-20 октября 2023 г.) // Республиканское инновационное унитарное предприятие «Научно-технологический парк БНТУ «Политехник» ; сост. М. А. Войтешонок. – Минск : БНТУ, 2023. – С. 65-66.
Abstract
Medical image segmentation has a vital role in disease diagnosis and treatment. The feature enhancement module and a mask embedding block for medical image segmentation is proposed. This method utilizes an encoder-decoder architecture with attention mechanism and residual connections to adaptively adjust the importance of each layer of features. The proposed network achieves stronger feature transfer and reconstruction, enhancing multi-scale expressive capabilities and context-awareness иy introducing dense skip connections Experimental results on three datasets demonstrate significant improvements in segmentation accuracy and robustness, particularly in handling segmentation details and boundaries.