Abstract
Medical imaging modalities produce large volume of digital data each day in modern healthcare. Several techniques have been proposed for volumetric medical image data compression. In this paper, we present a novel wavelet-based visually lossless coding scheme for the compression of volumetric magnetic resonance imaging (MRI) and computed tomography (CT) images. A visual model is incorporated in the coder to identify and measure visually irrelevant information. Performance of the compression scheme is further improved by eliminating the slice redundancy. The obtained results show better compression ratio compared to results obtained with pixel-based visually lossless compression technique, without any degradation in visual quality. We compared the performance of proposed technique with standard state of the art compression codecs such as joint photographic experts group-lossless (JPEG-LS), JPEG-2000, JPEG-3D, H.264/MPEG-4 AVC, differential pulse code modulation (DPCM) and medical image lossless compression (MILC). Results show better compression ratio over that of standard lossless compression schemes without any perceivable distortion.
| Original language | English |
|---|---|
| Pages (from-to) | 644-668 |
| Number of pages | 25 |
| Journal | International Journal of Computational Vision and Robotics |
| Volume | 7 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2017 |
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Computer Science Applications
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