2013 Summer Project Week: Individualized Neuroimaging Content Analysis using 3D Slicer in Alzheimer's Disease

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  Projects List

Key Investigators

• USYD: Sidong Liu, Weidong (Tom) Cai
• BWH: Sonia Pujol, Ron Kikinis

Introduction

We have accumulated a wealth of knowledge learnt from the population-based research. Then how can we apply such knowledge to health care of individual patient? The target of current medical image computing is shifting from population-based analysis to subject-specific analysis.

Objective

The goal of this project is to present a novel way of applying our knowledge to subject-specific neuroimaging content analysis using 3D Slicer. As an example, we will demonstrate some analysis results of a group of Alzheimer's patients.

Approach, Plan

There are three key steps of personalized medicine. First, the medical knowledge should be encoded in certain way, so that it can be integrated into current research platform seamlessly. Second, we need to translate such knowledge and apply it to the needs of individual subjects. Finally, the individualized analysis is also an importance source of information, which might provide us a better understanding of the disease and help to extend our knowledge.

Progress

In our pervious studies, we have proposed a range of medical knowledge encoding and decoding methods, including voxel-based degenerative t-maps (ICIP 2010), sparse-autoencoded brain atrophy templates (SNM 2013, EMBC 2013), and biomarker-based disease-sensitive kernels (MICCAI 2013).

Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

1. ITK Module
2. Slicer Module
   1. Built-in
   2. Extension -- commandline
   3. Extension -- loadable ("YES")
3. Other (Please specify)

References

• Cai, W., Liu, S., Wen, L., Eberl, S., Fulham, M., Feng, D.: 3D Neurological Image Retrieval with Localized Pathology-Centric CMRGLC Patterns. In: The IEEE 17th International Conference on Image Processing (ICIP 2010), pp. 3201-3204, Hong Kong (2010)
• Liu, S., Cai, W., Song, Y., Pujol, S., Kikinis, R., Wen, L., Feng, D.: Sparse Auto-encoded Hypo-metabolism Patterns in Alzheimer's Disease and Mild Cognitive Impairment. The Journal of Nuclear Medicine (Abstract) (Accepted)
• Liu, S., Cai, W., Song, Y., Pujol, S., Kikinis, R., Feng, D.: Localized Sparse Code Gradient in Alzheimer's Disease Staging. In: The 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Osaka, Japan (2013)
• Liu, S., Song, Y., Cai, W., Pujol, S., Kikinis, R., Wang, X., Feng, D.: Multifold Bayesian Kernelization in Alzheimer’s Diagnosis. In: MICCAI 2013, Nagoya, Japan (Accepted)