2022 Fiscal Year Research-status Report
A convolutional neural network based approach for generating full PET/CT image series from shorter scan time
| Project/Area Number |
19K20685
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| Research Institution | National Institutes for Quantum Science and Technology |
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Principal Investigator |
BhusalChhatkuli Ritu 国立研究開発法人量子科学技術研究開発機構, 量子医科学研究所 分子イメージング診断治療研究部, 博士研究員 (50836591)
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| Project Period (FY) |
2019-04-01 – 2024-03-31
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| Keywords | PET/CT / Prediction / Neural Network / CNN-LSTM |
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| Outline of Annual Research Achievements |
Successful generation of delayed images and comparison with actual delayed images using CNN-LSTM based neural network.-Summarizing research and statistical analysis for the publication in journal.-Writing journal paper for the part of research and submitting to the journal.-Reviewing the writing according to the comments from the reviewers and repeat the analysis for the part of the research. Currently in the process of revision.
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| Current Status of Research Progress |
Current Status of Research Progress
3: Progress in research has been slightly delayed.
Reason
Slight delayed in publication of manuscript due to some ethical concerns and review and resubmission in journals.
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| Strategy for Future Research Activity |
Correction of the manuscript according to the reviewers and its publication in the journal.
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| Causes of Carryover |
Publishing paper, attending conferences, buying software for analysis etc.
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