| Project/Area Number |
19K20685
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 90110:Biomedical engineering-related
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| Research Institution | Chiba University (2023)
National Institutes for Quantum Science and Technology (2019-2022) |
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Principal Investigator |
BhusalChhatkuli Ritu 千葉大学, 子どものこころの発達教育研究センター, 特任助教 (50836591)
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| Project Period (FY) |
2019-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2023)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2021: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2020: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2019: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
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| Keywords | PET/CT / CNN-LSTM / Neural Network / Prediction / dynamic images / RNN / list mode PET / neural networks / image generation / CNN / time series / prediction |
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| Outline of Research at the Start |
In recent years, machine learning and deep learning has become a subject of interest for many researchers worldwide. Whereas, CNN have become a methodology of choice for analyzing medical images. In this research, we propose a CNN based approach for generating PET/CT image series for malignant tumors in pancreas in shorter scan time. The images are currently obtained during the delayed scan during the regular PET/CT imaging analysis.
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| Outline of Annual Research Achievements |
Initial and delayed scans, also known as dual-time-point scans, are widely used in positron emission tomography/computed tomography (PET/CT) for the diagnosis and delineation of pancreatic cancer; however, their acquisition is relatively time-consuming. The purpose of this pilot study was to use neural network based method to eliminate the need of delayed PET/CT scan for diagnosis. The results obtained from our CNN-LSTM based analysis suggested that our study could obviate the need for delayed scans however validations studies are required for the clinical application of our model.
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| Current Status of Research Progress |
Current Status of Research Progress
4: Progress in research has been delayed.
Reason
The pilot study (Data acquisition and analysis) has been completed and the journal paper was submitted, unfortunately it could not be accepted hence we are currently correcting the manuscript and preparing for submission in other journal.
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| Strategy for Future Research Activity |
Currently the manuscript is being prepared for this work and is to be submitted in a scientific journal.
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