Difference between revisions of "2015 Summer Project Week:BigDataFeatures"
From NAMIC Wiki
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[[File:Lung-ct.png|300px|thumb|left|Lung CT Features]] | [[File:Lung-ct.png|300px|thumb|left|Lung CT Features]] | ||
[[File:3D_SIFT_Prostate.png|300px|thumb|left|Prostate US Features]] | [[File:3D_SIFT_Prostate.png|300px|thumb|left|Prostate US Features]] | ||
| − | [[File:Img-feat.png|300px|thumb|left|Data Reduction]] | + | [[File:Img-feat.png|300px|thumb|left|Data Reduction for 20000 lung CT volumes]] |
==Project Description== | ==Project Description== | ||
Revision as of 09:19, 22 June 2015
Home < 2015 Summer Project Week:BigDataFeatures
Key Investigators
- Matthew Toews, École de Technologie Supérieure
- William Wells, BWH, Harvard Medical School
- Raul San Jose Estepar, BWH, Harvard Medical School
- Tina Kapur, BWH, Harvard Medical School
Previous Work: 3D SIFT-Rank Visualization, SLC 2015
Project Description
Objective
- This project will investigate the use of 3D SIFT-RANK image features for organizing and deriving information from 3D medical image volumes.
- Technology: invariant feature extraction, descriptor representation.
- Application domains: registration, segmentation, classification.
- Image domains: lung CT, brain MR, prostate and brain ultrasound.
- Clinical use case scenarios: chronic obstructive pulmonary disease, Alzheimer's disease, cancer.
Approach, Plan
- Discussion and documentation
- Algorithms: fast KNN methods, hashing, robust estimation (RANSAC, Hough transform).
- Mathematical formalisms: probabilistic inference, kernel methods, manifold learning.
Progress
References
[1] SIFT View, NAMIC 2015 SLC Project Week
[2] "A Feature-based Approach to Big Data Analysis of Medical Images", M. Toews, C. Wachinger, R. S. J. Estepar, W.M. Wells III.
Information Processing in Medical Imaging (IPMI), 2015.
[3] "Keypoint Transfer Segmentation", C. Wachinger, M. Toews, G. Langs, W.M. Wells IIIi, P. Golland. Information Processing in Medical Imaging (IPMI), 2015.
