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[Automatic detection method of intracranial aneurysms on maximum intensity projection images based on SE-CaraNet].
Bai, Peirui; Song, Xuefeng; Liu, Qingyi; Liu, Jiahui; Cheng, Jin; Xiu, Xiaona; Ren, Yande; Wang, Chengjian.
Afiliação
  • Bai P; School of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China.
  • Song X; School of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China.
  • Liu Q; School of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China.
  • Liu J; School of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China.
  • Cheng J; School of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China.
  • Xiu X; School of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, P. R. China.
  • Ren Y; Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong 265000, P. R. China.
  • Wang C; Department of Radiology, Affiliated Hospital of Qingdao University, Qingdao, Shandong 265000, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 41(2): 228-236, 2024 Apr 25.
Article em Zh | MEDLINE | ID: mdl-38686402
ABSTRACT
Conventional maximum intensity projection (MIP) images tend to ignore some morphological features in the detection of intracranial aneurysms, resulting in missed detection and misdetection. To solve this problem, a new method for intracranial aneurysm detection based on omni-directional MIP image is proposed in this paper. Firstly, the three-dimensional magnetic resonance angiography (MRA) images were projected with the maximum density in all directions to obtain the MIP images. Then, the region of intracranial aneurysm was prepositioned by matching filter. Finally, the Squeeze and Excitation (SE) module was used to improve the CaraNet model. Excitation and the improved model were used to detect the predetermined location in the omni-directional MIP image to determine whether there was intracranial aneurysm. In this paper, 245 cases of images were collected to test the proposed method. The results showed that the accuracy and specificity of the proposed method could reach 93.75% and 93.86%, respectively, significantly improved the detection performance of intracranial aneurysms in MIP images.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Aneurisma Intracraniano / Angiografia por Ressonância Magnética / Imageamento Tridimensional Limite: Humans Idioma: Zh Revista: Sheng Wu Yi Xue Gong Cheng Xue Za Zhi / Sheng wu yi xue gong cheng xue za zhi Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Aneurisma Intracraniano / Angiografia por Ressonância Magnética / Imageamento Tridimensional Limite: Humans Idioma: Zh Revista: Sheng Wu Yi Xue Gong Cheng Xue Za Zhi / Sheng wu yi xue gong cheng xue za zhi Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2024 Tipo de documento: Article