| 研究課題/領域番号 |
19K20685
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| 研究機関 | 国立研究開発法人量子科学技術研究開発機構 |
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研究代表者 |
BhusalChhatkuli Ritu 国立研究開発法人量子科学技術研究開発機構, 放射線医学総合研究所 分子イメージング診断治療研究部, 博士研究員(任非) (50836591)
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| 研究期間 (年度) |
2019-04-01 – 2022-03-31
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| キーワード | Neural Network / PET/CT / list mode PET / RNN / Prediction |
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| 研究実績の概要 |
-Acquisition of patient data from the hospital, data preprocessing and mining.
-Using Convolutional Neural Network and recurrent neural network for creating the prediction model for predicting delayed image slices. Prediction using early PET images and dynamic images.
-Successful prediction of delayed images.Qualitative and quantitative analysis.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
3: やや遅れている
理由
Delayed in obtaining significant results from the prediction models. Slight change in the approach.
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| 今後の研究の推進方策 |
-Completing the quantitative analysis based on the requirement from the doctors in the hospital.
-Submitting the result to conference.
- Publishing the paper
-Analysis with the new set of data acquired from the newly installed PET/Imaging device in hospital
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| 次年度使用額が生じた理由 |
Several society attendance was cancelled due to the ongoing covid-19 pandemic.
Due to the less number of data, the previously bought server was enough for calculation so far but will have to buy big machine in future once the data increases.
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