Title:
MEDICAL IMAGE DIAGNOSTICS ASSISTANCE DEVICE, MEDICAL IMAGE DIAGNOSTICS ASSISTANCE METHOD, AND PROGRAM
Document Type and Number:
WIPO Patent Application WO/2023/047963
Kind Code:
A1
Abstract:
A medical image diagnostics assistance device (1) comprises: a classification model (1A) for classifying at least presence or absence of disease from a medical image; a prediction unit (11) that carries out prediction using the classification model (1A); and a learning unit (12) that carries out supervised learning of the classification model (1A). The supervised learning uses a training medical image for which at least presence or absence of disease is known as teacher data. The classification model (1A) is composed of a convolutional neural network (1A1) and an attention branch network (1A2) that visualizes a region of interest of the convolutional neural network (1A1). At the stage of carrying out the supervised learning, the attention branch network (1A2) is given preliminary information indicating a classification region, which is a region in the training medical image required for classification of presence or absence of disease.
Inventors:
KOTOKU JUNICHI (JP)
TSUJI TAKUMASA (JP)
TSUJI TAKUMASA (JP)
Application Number:
PCT/JP2022/033653
Publication Date:
March 30, 2023
Filing Date:
September 08, 2022
Export Citation:
Assignee:
UNIV TEIKYO (JP)
International Classes:
G06T7/00; A61B6/00; A61B6/03
Domestic Patent References:
| WO2022172817A1 | 2022-08-18 |
Foreign References:
| JP6657480B2 | 2020-03-04 | |||
| JP2021022368A | 2021-02-18 | |||
| JP2020119154A | 2020-08-06 | |||
| US20210150728A1 | 2021-05-20 | |||
| US20190362183A1 | 2019-11-28 | |||
| JPH06251038A | 1994-09-09 | |||
| US20210090247A1 | 2021-03-25 | |||
| JP2018117883A | 2018-08-02 | |||
| US10430946B1 | 2019-10-01 | |||
| JP2021153427A | 2021-10-07 | |||
| JP6657480B2 | 2020-03-04 |
Other References:
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S. JAEGER ET AL.: "Automatic Tuberculosis Screening Using Chest Radiographs", IEEE TRANS. MED. IMAGING, vol. 33, no. 2, pages 233 - 245, XP011538614, DOI: 10.1109/TMI.2013.2284099
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B. VAN GINNEKENM. B. STEGMANNM. LOOG: "Segmentation of anatomical structures in chest radiographs using supervised methods: A comparative study on a public database", MED. IMAGE ANAL, vol. 10, no. 1, 2006, pages 19 - 40, XP005205979, DOI: 10.1016/j.media.2005.02.002
OLAF, RONNEBERGER ET AL.: "U-Net: Convolutional Networks for Biomedical Image Segmentation", MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2015, 2015, pages 234 - 241, XP055561106, DOI: 10.1007/978-3-319-24574-4_28
FUKUI, Hiroshi et al. Attention Branch Network: Learning of Attention Mechanism for Visual Explanation. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2019, pp. 10697-10706, [retrieval date: 05 October 2022],
H. FUKUIT. HIRAKAWAT. YAMASHITAH. FUJIYOSHI: "Attention branch network: Learning of attention mechanism for visual explanation", PROC. IEEE COMPUT. SOC. CONF. COMPUT. VIS. PATTERN RECOGNIT, vol. 2019, 2019, pages 10697 - 10706
O. RONNEBERGERP. FISCHERT. BROX: "U-net: Convolutional networks for biomedical image segmentation", LECT. NOTES COMPUT. SCI. (INCLUDING SUBSER. LECT. NOTES ARTIF. INTELL. LECT. NOTES BIOINFORMATICS, vol. 9351, 2015, pages 234 - 241
S. CANDEMIR ET AL.: "Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration", IEEE TRANS. MED. IMAGING, vol. 33, no. 2, 2014, pages 577 - 590, XP055230333, DOI: 10.1109/TMI.2013.2290491
S. JAEGER ET AL.: "Automatic Tuberculosis Screening Using Chest Radiographs", IEEE TRANS. MED. IMAGING, vol. 33, no. 2, pages 233 - 245, XP011538614, DOI: 10.1109/TMI.2013.2284099
C. JUNJI SHIRAISHI ET AL.: "Standard Digital Image Database:Chest Lung Nodules and Non-Nodules Created", THE JAPANESE SOCIETY OF RADIOLOGICAL TECHNOLOGY (JSRT) IN COOPERATION WITH THE JAPANESE RADIOLOGICAL SOCIETY (JRS, 1997
B. VAN GINNEKENM. B. STEGMANNM. LOOG: "Segmentation of anatomical structures in chest radiographs using supervised methods: A comparative study on a public database", MED. IMAGE ANAL, vol. 10, no. 1, 2006, pages 19 - 40, XP005205979, DOI: 10.1016/j.media.2005.02.002
Attorney, Agent or Firm:
TAZAKI Akira et al. (JP)
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