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International Journal of Radiation Research، جلد ۲۲، شماره ۱، صفحات ۹-۱۵
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی A computerized tomography based deep learning diagnostic method of maxillary sinus fungal balls
چکیده انگلیسی مقاله
Background: Traditional diagnostic methods are limited in accuracy when detecting maxillary sinus fungal balls, leading to a higher risk of misdiagnosis or missed diagnosis. This study focuses on a deep learning-based algorithm for assisting in the localization and diagnosis of maxillary sinus fungal balls, addressing the limitations of conventional diagnostic procedures. Materials and Methods: Axial CT imaging data of maxillary sinus were collected from 107 patients, including 47 cases of maxillary sinus fungal balls, 30 cases of other maxillary sinus lesions and 30 cases of healthy maxillary sinus, based on which, a dataset was constructed and a two-stage assisted diagnosis algorithm consisting of a classification and detection model was established. In the first stage, slices containing maxillary sinus were classified and selected. In the second stage, the selected slices were detected to diagnose and localize the fungal ball lesions in the maxillary sinus. Results: The accuracy of the classification model was 92.71%, the mAP and AP50 of the detection model were 0.73 and 0.76, respectively, and the accuracy of the algorithm for the diagnosis of maxillary sinus fungal balls was 84.4%. Conclusion: It is feasible to develop a two-stage auxiliary diagnosis method for maxillary sinus fungal ball based on deep learning.
کلیدواژه‌های انگلیسی مقاله Maxillary sinus, fungal ball, computed tomography, deep learning, convolutional neural network.
نویسندگان مقاله | L. Peng
Department of Otolaryngology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201318, China


| R. Shi
Department of Otolaryngology Head and Neck Surgery, Shanghai 9th People’s Hospital/Shanghai Ninth People’s Hospital, School of medicine, Shanghai Jiao Tong University, Shanghai 200011, China


| R. Shi
Department of Otolaryngology Head and Neck Surgery, Shanghai 9th People’s Hospital/Shanghai Ninth People’s Hospital, School of medicine, Shanghai Jiao Tong University, Shanghai 200011, China


| H. Kong
Inspection Technology Laboratory, Intelligent Manufacturing Research Center of Midea Group, Shanghai 201702, China


| W. Duan
Department of Otolaryngology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201318, China


| W. Duan
Department of Otolaryngology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201318, China


| L. Zhu
Department of Otolaryngology, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Shanghai 201318, China
نشانی اینترنتی http://ijrr.com/browse.php?a_code=A-10-1-1131&slc_lang=en&sid=1
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کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده Radiation Biology
نوع مقاله منتشر شده تحقیق بدیع
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