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Position Prior Attention Network for Pancreas Tumor Segmentation.
Dong, Kaiqi; Hu, Peijun; Li, Xiang; Tian, Yu; Zhu, Yan; Bai, Xueli; Liang, Tingbo; Li, Jingsong.
Afiliación
  • Dong K; Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
  • Hu P; Research Center for Healthcare Data Science, Zhejiang Laboratory, Hangzhou, China.
  • Li X; Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Tian Y; Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
  • Zhu Y; Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
  • Bai X; Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Liang T; Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Li J; Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Stud Health Technol Inform ; 310: 951-955, 2024 Jan 25.
Article en En | MEDLINE | ID: mdl-38269949
ABSTRACT
Segmentation of pancreatic tumors on CT images is essential for the diagnosis and treatment of pancreatic cancer. However, low contrast between the pancreas and the tumor, as well as variable tumor shape and position, makes segmentation challenging. To solve the problem, we propose a Position Prior Attention Network (PPANet) with a pseudo segmentation generation module (PSGM) and a position prior attention module (PPAM). PSGM and PPAM maps pancreatic and tumor pseudo segmentation to latent space to generate position prior attention map and supervises location classification. The proposed method is evaluated on pancreatic patient data collected from local hospital and the experimental results demonstrate that our method can significantly improve the tumor segmentation results by introducing the position information in the training phase.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Pancreáticas Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Pancreáticas Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos