Synthesizing Brain Images Using Deep Learning

The performance of image-generation artificial intelligence using deep neural networks has significantly improved. This article presents an overview of the technology driving these advancements and explores its potential applications in brain research. The article also discusses how state-of-the-art generative models can create realistic brain images as data, highlighting their potential for future research.

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Publication Details

Journal
Japanese Journal of Physiological Psychology and Psychophysiology
Published
2024-09-19
DOI
https://doi.org/10.5674/jjppp.2410si
Citations
2
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.49
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article

Synthesizing Brain Images Using Deep Learning

Masahiro Takamura
2 citations
Japanese Journal of Physiological Psychology and Psychophysiology
Brain Tumor Detection and Classification
0.49
article

Synthesizing Brain Images Using Deep Learning

Masahiro Takamura
article en
2 citations

Abstract

The performance of image-generation artificial intelligence using deep neural networks has significantly improved. This article presents an overview of the technology driving these advancements and explores its potential applications in brain research. The article also discusses how state-of-the-art generative models can create realistic brain images as data, highlighting their potential for future research.

Japanese Journal of Physiological Psychology and PsychophysiologyVol. 42(2)
Fujita Health University (JP)
Openalex Percentile: Top 34%
Brain Tumor Detection and Classification
0.49
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Synthesizing Brain Images Using Deep Learning — Masahiro Takamura · Japanese Journal of Physiological Psychology and Psychophysiology (2024) | TGRS Research Map | TGRS