Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Enc
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Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding Shuyu Yang Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409-3102, USA Email: [email protected]
Sunanda Mitra Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409-3102, USA Email: [email protected]
Enrique Corona Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409-3102, USA Email: [email protected]
Brian Nutter Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409-3102, USA Email: [email protected]
D. J. Lee Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT 84602, USA Email: [email protected] Received 31 March 2002 and in revised form 25 October 2002 Many common modalities of medical images acquire high-resolution and multispectral images, which are subsequently processed, visualized, and transmitted by subsampling. These subsampled images compromise resolution for processing ability, thus risking loss of significant diagnostic information. A hybrid multiresolution vector quantizer (HMVQ) has been developed exploiting the statistical characteristics of the features in a multiresolution wavelet-transformed domain. The global codebook generated by HMVQ, using a combination of multiresolution vector quantization and residual scalar encoding, retains edge information better and avoids significant blurring observed in reconstructed medical images by other well-known encoding schemes at low bit rates. Two specific image modalities, namely, X-ray radiographic and magnetic resonance imaging (MRI), have been considered as examples. The ability of HMVQ in reconstructing high-fidelity images at low bit rates makes it particularly desirable for medical image encoding and fast transmission of 3D medical images generated from multiview stereo pairs for visual communications. Keywords and phrases: high fidelity hybrid encoding, global codebook, low bit rate, multilevel wavelet feature statistics, efficient retrieval of high-resolution medical images.
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INTRODUCTION
Large volumes of digitized radiographic images accumulated in hospitals and educational institutes pose a challenge in image database management, requiring high fidelity and image modality-specific compression approaches. Such level of image management necessitates a system that provides easy access and high fidelity reconstruction. The use of image compression for fast medical image retrieval is a debatable subject
since high compression ratios usually introduce critical information loss that might impede accurate diagnosis. However, requirements for image quality also differ depending on applications. It is therefore desirable to construct a flexible image management system that can cater to the specific needs of its users. The system should address important issues such as user-preferred image resolution and scale and transmissio
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