M
Michihito Nozawa
Researcher at Aichi Gakuin University
Publications - 17
Citations - 543
Michihito Nozawa is an academic researcher from Aichi Gakuin University. The author has contributed to research in topics: Osteonecrosis of the jaw & Cervical lymph nodes. The author has an hindex of 8, co-authored 16 publications receiving 275 citations.
Papers
More filters
Journal ArticleDOI
Deep-learning classification using convolutional neural network for evaluation of maxillary sinusitis on panoramic radiography
Makoto Murata,Yoshiko Ariji,Yasufumi Ohashi,Taisuke Kawai,Motoki Fukuda,Takuma Funakoshi,Yoshitaka Kise,Michihito Nozawa,Akitoshi Katsumata,Hiroshi Fujita,Eiichiro Ariji +10 more
TL;DR: The diagnostic performance of the deep-learning system for maxillary sinusitis on panoramic radiographs was sufficiently high and is expected to provide diagnostic support for inexperienced dentists.
Journal ArticleDOI
Contrast-enhanced computed tomography image assessment of cervical lymph node metastasis in patients with oral cancer by using a deep learning system of artificial intelligence.
Yoshiko Ariji,Motoki Fukuda,Yoshitaka Kise,Michihito Nozawa,Yudai Yanashita,Hiroshi Fujita,Akitoshi Katsumata,Eiichiro Ariji +7 more
TL;DR: The deep learning image classification system yielded diagnostic results similar to those of the radiologists, which suggests that this system may be valuable for diagnostic support.
Journal ArticleDOI
Automatic detection and classification of radiolucent lesions in the mandible on panoramic radiographs using a deep learning object detection technique.
Yoshiko Ariji,Yudai Yanashita,Syota Kutsuna,Chisako Muramatsu,Motoki Fukuda,Yoshitaka Kise,Michihito Nozawa,Chiaki Kuwada,Hiroshi Fujita,Akitoshi Katsumata,Eiichiro Ariji +10 more
TL;DR: Radiolucent lesions of the mandible can be detected with high sensitivity using deep learning and the best combination of detection and classification sensitivity occurred with dentigerous cysts.
Journal ArticleDOI
Performance of deep learning object detection technology in the detection and diagnosis of maxillary sinus lesions on panoramic radiographs.
Ryosuke Kuwana,Yoshiko Ariji,Motoki Fukuda,Yoshitaka Kise,Michihito Nozawa,Chiaki Kuwada,Chisako Muramatsu,Akitoshi Katsumata,Hiroshi Fujita,Eiichiro Ariji +9 more
TL;DR: This study indicated that the detection sensitivities of maxillary sinuses were high and the performance ofmaxillary sinus lesion identification was ≧80%.
Journal ArticleDOI
CT evaluation of extranodal extension of cervical lymph node metastases in patients with oral squamous cell carcinoma using deep learning classification
Yoshiko Ariji,Yoshihiko Sugita,Toru Nagao,Atsushi Nakayama,Motoki Fukuda,Yoshitaka Kise,Michihito Nozawa,Masako Nishiyama,Akitoshi Katumata,Eiichiro Ariji +9 more
TL;DR: The deep learning diagnostic performance in extranodal extension was significantly higher than that of radiologists and is expected to improve diagnostic accuracy by further study with increasing the number of patients.