Diagnosing brain tumours through functional imaging and machine learning

The thesis is expected to be open to public when everything listed below gets successfully published.

• § 1 Introduction
• § 2 Background
  • § 2.1 Common childhood brain tumour
  • § 2.2 Brain tumour metabolism ▢
• § 3 Theory
  • § 3.1 Magnetic resonance
  • § 3.2 MR pulse sequences
  • § 3.3 Proton MR spectroscopy
  • § 3.4 Diffusion MR imaging
  • § 3.5 Wavelets
  • § 3.6 Machine learning
  • § 3.7 Statistic analysis
• § 4 Literature review ▢
• § 5 Methodology
  • § 5.1 Adaptive Wavelet Noise Suppression ◯
  • § 5.2 Semi-Synthetic Wavelet Oversampling △
• § 6 Phantom Validation for AWNS ◯
• § 7 Metabolite Selection for Tumour Classification ◉ → Published version
• § 8 Metabolite Based Tumour Classification with AWNS ◉ → Published version
• § 9 Metabolite Based Tumour Classification with SSWO △
• § 10 Spectrum Based Tumour Classification with AWNS △
• § 11 Multi-Modal Imaging Based Tumour Classification ◎
• § 12 Conclusions

---

• ◉ Research article published.
• ◎ Research article under revision.
• ◯ Research article in preparation.
• ▢ Review article in preparation.
• △ Published as an ISMRM abstract and will be expanded into a full article after completing others.