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Contextual encoding in uniform and adaptive mesh-based lossless compression of MR images
1Department of Electrical Engineering, Indian Institute of Science, Bangalore 560012, India. srikanthryali@yahoo.co.uk
IEEE Transactions on Medical Imaging
|September 15, 2005
Summary
Novel mesh-based coding improves 3-D brain MRI compression. New methods achieve bit rates comparable to advanced wavelet schemes, offering efficient lossless compression for medical imaging.
Area of Science:
- Medical Imaging
- Computer Vision
- Data Compression
Background:
- 3-D brain magnetic resonance imaging (MRI) requires efficient compression techniques.
- Existing mesh-based coding schemes can be improved for clinical relevance and accuracy.
Purpose of the Study:
- To introduce and evaluate novel improvements to mesh-based coding for 3-D brain MRI.
- To enhance compression efficiency and clinical applicability of mesh-based schemes.
Main Methods:
- Eliminating irrelevant background for brain-only meshing.
- Implementing adaptive mesh generation using spatial edges and optical flow.
- Addressing the aperture problem in motion vector estimation.
- Utilizing context-based entropy coding after affine motion compensation.
Main Results:
- Achieved lossless compression rates of approximately 2 bits per voxel.
- Demonstrated comparable performance to state-of-the-art 3-D wavelet-based schemes.
- Showed effectiveness for 3-D brain computed tomography (CT) data compression.
- Adaptive mesh schemes offered marginal improvement over uniform schemes.
Conclusions:
- The proposed mesh-based coding improvements enhance 3-D brain MRI compression.
- These methods provide competitive lossless compression ratios for medical images.
- Mesh-based coding is a viable and effective approach for 3-D medical image compression.
