Surgical Workflow, Medical Imaging, Computer-Aided Surgery, Machine Learning for Medical Applications
One of the interesting talks in the Generative and Discriminative Learning for Medical Imaging
Tutorial in the last MICCAI 2014
was presented by Jerry Prince
regarding Image Synthesis and cross-modalities
, motivating us to work on such a challenging topic. In our project for MLMI
course, we would like to implement kind of Supervised Dictionary Learning incorporating the global consistency, discriminative labeling, and the Transformation-invariant.
Visit our lab at Garching.
internal project page
Please contact Shadi Albarqouni
for available student projects within this research project.
| Phase || Period || Conducted by || Materials || Results so far |
| Sparse Coding and Dictionary Learning || 06-14 Nov || all || Slides I |
| Locally-constrained Linear Coding || 14 Nov - 10 Dec || Christoph & Chandra || Paper: CVPR 2010 |
| Mid-term Presentation |
| Label Consistant/Discriminative Dictionary Learning || 10 Dec - 18 Dec || Christoph & Chandra || Paper: BMVC 2013 |
Paper: CVPR 2011
| Transformation Invariant Dictionary Learning || - || - || Paper: ICASSP 2014 || |
| Bonus: Mapping || 18 Dec - 23 Jan || Christoph & Chandra || Linear Mapping |
Iterative Linear Mapping
| Final Report |
What you are going to learn:
- Sparse Coding and Dictionary Learning
- Figure out the global consistency with different similarity measures.
- Figure out rotation and shift invariant dictionary