AI approach of cycle-consistent generative adversarial networks to synthesize PET images to train computer-aided diagnosis algorithm for dementia

Objective An artificial intelligence (AI)-based algorithm typically requires a considerable amount of training data; however, few training images are available for dementia with Lewy bodies and frontotemporal lobar degeneration. Therefore, this study aims to present the potential of cycle-consistent...

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Bibliographic Details
Published in:Annals of nuclear medicine 2020-07, Vol.34 (7), p.512-515
Main Authors: Kimura, Yuichi, Watanabe, Aya, Yamada, Takahiro, Watanabe, Shogo, Nagaoka, Takashi, Nemoto, Mitsutaka, Miyazaki, Koichi, Hanaoka, Kohei, Kaida, Hayato, Ishii, Kazunari
Format: Article
Language:English
Subjects:
Algorithms
Amyloid
Artificial intelligence
Degeneration
Dementia
Dementia - diagnostic imaging
Dementia disorders
Diagnosis
Diagnosis, Computer-Assisted
Frontotemporal dementia
Generative adversarial networks
Humans
Image Processing, Computer-Assisted - methods
Imaging
Lewy bodies
Medical diagnosis
Medicine
Medicine & Public Health
Neural Networks, Computer
Nuclear Medicine
Positron emission
Positron-Emission Tomography
Radiology
Short Communication
Synthesis
Tomography
Training
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Summary:Objective An artificial intelligence (AI)-based algorithm typically requires a considerable amount of training data; however, few training images are available for dementia with Lewy bodies and frontotemporal lobar degeneration. Therefore, this study aims to present the potential of cycle-consistent generative adversarial networks (CycleGAN) to obtain enough number of training images for AI-based computer-aided diagnosis (CAD) algorithms for diagnosing dementia. Methods We trained CycleGAN using 43 amyloid-negative and 45 positive images in slice-by-slice. Results The CycleGAN can be used to synthesize reasonable amyloid-positive images, and the continuity of slices was preserved. Discussion Our results show that CycleGAN has the potential to generate a sufficient number of training images for CAD of dementia.
ISSN:0914-7187
1864-6433
DOI:10.1007/s12149-020-01468-5