Age Estimation Summary

JoJo2013.1.11

Age Estimation Summary

• Idea• MeetingMICCAIMLMI• Journal• Conclusion

Idea

• Surface-based features are more sensitive to VBM in age estimation

• Franke, (2010), NeuroImage

Meeting (MICCAI)

Meeting (MICCAI)

• Work time: 2.4 – 3.1

• Work details: subject choose, data processing, learn toolbox, code, experiments, paper

• Mistakes:ML codeTime & paper writing

Reject！（ April

15）

Meeting (MLMI)

• SPIE(abstract 7.30deadline) MLMI (6.17 deadline 7.6 result)

• Great progress: pick up right subjects

Meeting (MLMI)

• What I learned:Follow the information about our areaCommunicationPaper writing(Logic)

Journal

• Brown, (2012.8), Current Biology (Leemon)• Experiment results are good.

Journal

• Extend: (Analyze the pattern we find)1 Dimension

Journal

• Extend: (Analyze the pattern we find)2 Why surface area is not included in the pattern

Journal

• Extend: (Analyze the pattern we find)3 Reliability of the pattern

(years: MeanSD) IXI database INDI database

Age range 20-82 2-22

4.570.04 1.380.02

5.570.04 1.770.02

0.940.01 0.790.01

Journal

• Extend: (Analyze the pattern we find)4 Application of the pattern

CV Accuarcy Sensitivity/Specificity J-statistic

Young/Old 97.77% 97.30/98.10% 0.9540

Journal

• What I learned:Record what you do everyday.Experiments is different from paper writing.Figure is very important. How to plot?Paper must be revised over and over.LogicFollow new workRelevant paper reading and summaryTime

Journal

Journal

Conclusion

• Achieve my goal

• Time-consuming

Thank you!!