Difference between revisions of "2015 Summer Project Week:BigDataFeatures"
From NAMIC Wiki
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* Raul San Jose Estepar, BWH, Harvard Medical School | * Raul San Jose Estepar, BWH, Harvard Medical School | ||
* Tina Kapur, BWH, Harvard Medical School | * Tina Kapur, BWH, Harvard Medical School | ||
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+ | ==3D SIFT-Rank Visualization - SLC 2015== | ||
+ | [[File:3D_SIFT_Lung.png|400px|thumb|left|Lung CT]] | ||
+ | [[File:3D_SIFT_Prostate.png|300px|thumb|left|Prostate US]] | ||
==Project Description== | ==Project Description== |
Revision as of 07:09, 22 June 2015
Home < 2015 Summer Project Week:BigDataFeaturesKey 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
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.