Medical Image Coding Research Articles

Interslice coding for medical three-dimensional images using an adaptive mode selection technique in wavelet transform domain

In this article the authors propose a novel interslice coding algorithm especially appropriate for medical 3-dimensional (3D) images. The proposed algorithm is based on a video coding algorithm using motion estimation/compensation and transform coding. In the algorithm, warping is adopted for motion compensation. Then, by using adaptive mode selection, an MC residual image and original image are mixed up in the wavelet transform domain for improvement in coding performance. The mixed image is then compressed by the zerotree coding method. It is proven that the adaptive mode selection technique in the wavelet transform domain is very useful for medical 3D image coding. Simulation results show that the proposed scheme provides good performance, regardless of interslice distance, and is prospective for medical 3D image compression.

9-10 参照画像を用いた医用静止画可逆符号化方式の改善

9-10 参照画像を用いた医用静止画可逆符号化方式の改善

Progressive lossless coding of medical images

The paper describes a procedure for lossless coding of medical images that uses a non-linear integer-to-integer wavelet transform generated by a lifting scheme and featuring progressive transmission capability. The quantization module implements a new modality for the coding of the wavelet coefficients that is more effective than the classical zerotree coding. Lossless image compression with progressive transmission capabilities plays a key role in medical image acquisition and handling. The contradictory requirements of exact data reconstruction possibility and of efficient and economic handling and transmission of large sets of images over large distances have to be met simultaneously. The experimental results, obtained on a set of 20 multimodal medical images, show that the algorithm outperforms other existing image lossless coding algorithms. Therefore it is a good candidate for telematics applications like teleradiology and PACS.

Medical image compression with lossless regions of interest

Many classes of images contain some spatial regions which are more important than other regions. Compression methods which are capable of delivering higher reconstruction quality for the important parts are attractive in this situation. For medical images, only a small portion of the image might be diagnostically useful, but the cost of a wrong interpretation is high. Algorithms which deliver lossless compression within the regions of interest, and lossy compression elsewhere in the image, might be the key to providing efficient and accurate image coding to the medical community. We present and compare several new algorithms for lossless region-of-interest (ROI) compression. One is based on lossless coding with the S-transform, and two are based on lossy wavelet zerotree coding together with either pixel-domain or transform-domain coding of the regional residual. We survey previous methods for region-based coding of medical images.

Simple space-varying least squares modelfor lossless medical image compression

The authors present a simple method for lossless predictive coding of medical images using two-dimensional space-varying least squares models. The performance of the proposed method is compared with that of a popular existing technique called HINT. The experimental results clearly indicate that the proposed scheme achieves higher compression compared to HINT with very little additional computational complexity.

Lossless compression of medical images using two-dimensional multiplicative autoregressive models

Presents new methods for lossless predictive coding of medical images using two dimensional multiplicative autoregressive models. Both single-resolution and multi-resolution schemes are presented. The performances of the proposed schemes are compared with those of four existing techniques. The experimental results clearly indicate that the proposed schemes achieve higher compression compared to the lossless image coding techniques considered.