Title:
MACHINE LEARNING DEVICE AND METHOD
Document Type and Number:
WIPO Patent Application WO/2019/167883
Kind Code:
A1
Abstract:
Provided are a machine learning device and method which enable machine learning of labeling, in which a plurality of labels are attached, at once and with a high degree of accuracy, to volume data using learning data having label attachments intermingled therein. A probability calculation unit (14) calculates, according to a teacher model (13a) in which learning has been completed, a value (soft label) indicating the likelihood of labeling a class Ci for each voxel of a second slice image. A detection unit (15) detects a "bronchial tube" and a "blood vessel" for the voxels of the second slice image by means of a commonly-known method such as a region expansion method, and performs labeling of the "bronchial tube" and the "blood vessel". A correction probability setting unit (16) replaces the soft label with a hard label of "bronchial tube" or "blood vessel", which was detected by the detection unit (15). A distillation unit (17) carries out distillation of a student model (18a) from the teacher model (13a) using the soft label after correction by the correction probability setting unit (16). Thereby, the student model (18a) in which learning was completed can be obtained.
Inventors:
KESHWANI DEEPAK (JP)
KITAMURA YOSHIRO (JP)
KITAMURA YOSHIRO (JP)
Application Number:
PCT/JP2019/007049
Publication Date:
September 06, 2019
Filing Date:
February 25, 2019
Export Citation:
Assignee:
FUJIFILM CORP (JP)
International Classes:
A61B6/03; G06N20/00; G06T7/00; G16H50/20
Foreign References:
| JP2017512091A | 2017-05-18 | |||
| JP2015112487A | 2015-06-22 |
Other References:
CHRISTODOULIDIS, STERGIOS: "Multisource Transfer Learning With Convolutional Neural Networks for Lung Pattern Analysis", IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, vol. 21, no. 1, 7 December 2016 (2016-12-07), pages 76 - 84, XP011640073, doi:10.1109/JBHI.2016.2636929
Attorney, Agent or Firm:
MATSUURA, Kenzo (JP)
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