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Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: From convolutional neural networks to visual transformers.
Liu, Wanli; Li, Chen; Rahaman, Md Mamunur; Jiang, Tao; Sun, Hongzan; Wu, Xiangchen; Hu, Weiming; Chen, Haoyuan; Sun, Changhao; Yao, Yudong; Grzegorzek, Marcin.
Afiliación
  • Liu W; Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
  • Li C; Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China. Electronic address: lichen@bmie.neu.edu.cn.
  • Rahaman MM; Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
  • Jiang T; School of Control Engineering, Chengdu University of Information Technology, Chengdu, 610225, China.
  • Sun H; Shengjing Hospital, China Medical University, Shenyang, 110001, China.
  • Wu X; Suzhou Ruiguan Technology Company Ltd., Suzhou, 215000, China.
  • Hu W; Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
  • Chen H; Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
  • Sun C; Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China; Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110169, China.
  • Yao Y; Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, 07030, USA.
  • Grzegorzek M; Institute of Medical Informatics, University of Luebeck, Luebeck, Germany.
Comput Biol Med ; 141: 105026, 2022 02.
Article en En | MEDLINE | ID: mdl-34801245
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias del Cuello Uterino / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Guideline Límite: Female / Humans Idioma: En Revista: Comput Biol Med Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias del Cuello Uterino / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Guideline Límite: Female / Humans Idioma: En Revista: Comput Biol Med Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos