Momoko MATSUYAMA

University of Electro-Communications

Papers

1

Total Citations

2

H-Index

1

About

Momoko Matsuyama is a pioneering researcher at the intersection of medical acoustics and deep learning, with a primary focus on advancing ultrasound-guided therapy. Her most notable contribution, detailed in her 2021 paper "A novel complementation method of an acoustic shadow region utilizing a convolutional neural network for ultrasound-guided therapy," addresses a critical limitation in ultrasound imaging: the acoustic shadowing that obscures targets during therapeutic procedures. By ingeniously applying a convolutional neural network to reconstruct these shadowed regions, Matsuyama has developed a computational framework that enhances image clarity and procedural accuracy, directly improving the safety and efficacy of non-invasive treatments. Though her work is early-stage, with two citations already reflecting its niche but growing relevance, this innovation positions her as a rising leader in medical AI. Her research bridges the gap between signal processing and clinical application, offering a scalable solution for real-time therapy guidance. Matsuyama’s dedication to solving practical imaging challenges underscores her potential to shape future ultrasound technologies, making her a researcher to watch in the evolving field of intelligent medical systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A novel complementation method of an acoustic shadow region utilizing a convolutional neural network for ultrasound-guided therapy
2 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of Electro-Communications

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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