TranSiam: Aggregating multi-modal visual features with locality for medical image segmentation

• Main Authors: LI, Xuejian, MA, Shiqiang, XU, Junhai, TANG, Jijun, HE, Shengfeng, GUO, Fei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Feature-level fusion; Local attention mechanism; Medical image segmentation; Multi-modal fusion; Graphics and Human Computer Interfaces; Health Information Technology
• Online Access: https://ink.library.smu.edu.sg/sis_research/8222; https://ink.library.smu.edu.sg/context/sis_research/article/9225/viewcontent/TranSiam_av.pdf
• Institution: Singapore Management University

Automatic segmentation of medical images plays an important role in the diagnosis of diseases. On single-modal data, convolutional neural networks have demonstrated satisfactory performance. However, multi-modal data encompasses a greater amount of information rather than single-modal data. Multi-mo...