Title:
OTITIS MEDIA DIAGNOSIS METHOD AND DEVICE
Document Type and Number:
WIPO Patent Application WO/2024/014702
Kind Code:
A1
Abstract:
An electronic device for diagnosing otitis media, according to one embodiment, comprises: a memory for storing computer-executable instructions, and a trained otitis media diagnosis model including a shared layer, which includes at least one convolution operation, and a plurality of classifier layers, which are connected to the shared layer; a processor accessing the memory so as to execute the instructions; a display electrically connected to the processor; and an image acquisition unit for receiving an otoendoscopic image of a patient, wherein the instructions can receive the otoendoscopic image of the patient, generate an input otoendoscopic image on the basis of a region of interest extracted from the received otoendoscopic image, extract feature data from the input otoendoscopic image on the basis of the shared layer, output, on the basis of a first classifier layer from among the plurality of classifier layers, disease prediction results for diseases belonging to a primary class from the extracted feature data, and individually output, on the basis of a plurality of second classifier layers separated from the first classifier layer from among the plurality of classifier layers, a single disease prediction result for each disease of diseases belonging to a secondary class, from the corresponding second classifier layer from among the plurality of second classifier layers.
Inventors:
KWEON JIHOON (KR)
AHN JOONG HO (KR)
CHAE JIHYE (KR)
PARK KEUNWOO (KR)
CHOI YEONJOO (KR)
AHN JOONG HO (KR)
CHAE JIHYE (KR)
PARK KEUNWOO (KR)
CHOI YEONJOO (KR)
Application Number:
PCT/KR2023/007254
Publication Date:
January 18, 2024
Filing Date:
May 26, 2023
Export Citation:
Assignee:
ASAN FOUND (KR)
UNIV ULSAN FOUND IND COOP (KR)
UNIV ULSAN FOUND IND COOP (KR)
International Classes:
A61B1/227; A61B1/00; G16H30/40; G16H50/20; G16H50/50
Foreign References:
| KR20210121119A | 2021-10-07 |
Other References:
ZENG XINYU, JIANG ZIFAN, LUO WEN, LI HONGGUI, LI HONGYE, LI GUO, SHI JINGYONG, WU KANGJIE, LIU TONG, LIN XING, WANG FUSEN, LI ZHEN: "Efficient and accurate identification of ear diseases using an ensemble deep learning model", SCIENTIFIC REPORTS, NATURE PUBLISHING GROUP, US, vol. 11, no. 1, 25 May 2021 (2021-05-25), US , XP093127418, ISSN: 2045-2322, DOI: 10.1038/s41598-021-90345-w
CHEN YEN-CHI, CHU YUAN-CHIA, HUANG CHII-YUAN, LEE YEN-TING, LEE WEN-YA, HSU CHIEN-YEH, YANG ALBERT C., LIAO WEN-HUEI, CHENG YEN-FU: "Smartphone-based artificial intelligence using a transfer learning algorithm for the detection and diagnosis of middle ear diseases: A retrospective deep learning study", ECLINICAL MEDICINE, vol. 51, 1 September 2022 (2022-09-01), pages 101543, XP093127419, ISSN: 2589-5370, DOI: 10.1016/j.eclinm.2022.101543
CHA DONGCHUL, PAE CHONGWON, SEONG SI-BAEK, CHOI JAE YOUNG, PARK HAE-JEONG: "Automated diagnosis of ear disease using ensemble deep learning with a big otoendoscopy image database", EBIOMEDICINE, ELSEVIER BV, NL, vol. 45, 1 July 2019 (2019-07-01), NL , pages 606 - 614, XP093127423, ISSN: 2352-3964, DOI: 10.1016/j.ebiom.2019.06.050
WU ZEBIN, LIN ZHEQI, LI LAN, PAN HONGGUANG, CHEN GUOWEI, FU YUQING, QIU QIANHUI: "Deep Learning for Classification of Pediatric Otitis Media", THE LARYNGOSCOPE, WILEY-BLACKWELL, UNITED STATES, vol. 131, no. 7, 1 July 2021 (2021-07-01), United States , pages E2344 - E2351, XP093127425, ISSN: 0023-852X, DOI: 10.1002/lary.29302
KHAN MOHAMMAD AZAM, KWON SOONWOOK, CHOO JAEGUL, HONG SEOK MIN, KANG SUNG HUN, PARK IL-HO, KIM SUNG KYUN: "Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks", NEURAL NETWORKS., ELSEVIER SCIENCE PUBLISHERS, BARKING., GB, vol. 126, 1 June 2020 (2020-06-01), GB , pages 384 - 394, XP093127426, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2020.03.023
CHOI YEONJOO, CHAE JIHYE, PARK KEUNWOO, HUR JAEHEE, KWEON JIHOON, AHN JOONG HO: "Automated multi-class classification for prediction of tympanic membrane changes with deep learning models", PLOS ONE, PUBLIC LIBRARY OF SCIENCE, US, vol. 17, no. 10, 10 October 2022 (2022-10-10), US , pages e0275846, XP093127429, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0275846
CHEN YEN-CHI, CHU YUAN-CHIA, HUANG CHII-YUAN, LEE YEN-TING, LEE WEN-YA, HSU CHIEN-YEH, YANG ALBERT C., LIAO WEN-HUEI, CHENG YEN-FU: "Smartphone-based artificial intelligence using a transfer learning algorithm for the detection and diagnosis of middle ear diseases: A retrospective deep learning study", ECLINICAL MEDICINE, vol. 51, 1 September 2022 (2022-09-01), pages 101543, XP093127419, ISSN: 2589-5370, DOI: 10.1016/j.eclinm.2022.101543
CHA DONGCHUL, PAE CHONGWON, SEONG SI-BAEK, CHOI JAE YOUNG, PARK HAE-JEONG: "Automated diagnosis of ear disease using ensemble deep learning with a big otoendoscopy image database", EBIOMEDICINE, ELSEVIER BV, NL, vol. 45, 1 July 2019 (2019-07-01), NL , pages 606 - 614, XP093127423, ISSN: 2352-3964, DOI: 10.1016/j.ebiom.2019.06.050
WU ZEBIN, LIN ZHEQI, LI LAN, PAN HONGGUANG, CHEN GUOWEI, FU YUQING, QIU QIANHUI: "Deep Learning for Classification of Pediatric Otitis Media", THE LARYNGOSCOPE, WILEY-BLACKWELL, UNITED STATES, vol. 131, no. 7, 1 July 2021 (2021-07-01), United States , pages E2344 - E2351, XP093127425, ISSN: 0023-852X, DOI: 10.1002/lary.29302
KHAN MOHAMMAD AZAM, KWON SOONWOOK, CHOO JAEGUL, HONG SEOK MIN, KANG SUNG HUN, PARK IL-HO, KIM SUNG KYUN: "Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks", NEURAL NETWORKS., ELSEVIER SCIENCE PUBLISHERS, BARKING., GB, vol. 126, 1 June 2020 (2020-06-01), GB , pages 384 - 394, XP093127426, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2020.03.023
CHOI YEONJOO, CHAE JIHYE, PARK KEUNWOO, HUR JAEHEE, KWEON JIHOON, AHN JOONG HO: "Automated multi-class classification for prediction of tympanic membrane changes with deep learning models", PLOS ONE, PUBLIC LIBRARY OF SCIENCE, US, vol. 17, no. 10, 10 October 2022 (2022-10-10), US , pages e0275846, XP093127429, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0275846
Attorney, Agent or Firm:
MUHANN PATENT & LAW FIRM (KR)
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