Learning-based parameter prediction for quality control in three-dimensional medical image compression

2021 ◽  
Vol 22 (9) ◽  
pp. 1169-1178
Author(s):  
Yuxuan Hou ◽  
Zhong Ren ◽  
Yubo Tao ◽  
Wei Chen
Keyword(s):  
Quality Control ◽  
Image Compression ◽  
Medical Image ◽  
Three Dimensional ◽  
Medical Image Compression ◽  
Parameter Prediction

scholarly journals IMPLEMENTATION METHOD ON MEDICAL IMAGE COMPRESSION SYSTEM: A REVIEW

2017 ◽  
Vol 79 (7) ◽  
Author(s):  
Azlan Muharam ◽  
Afandi Ahmad
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Medical Image ◽  
Rapid Development ◽  
Three Dimensional ◽  
Medical Image Processing ◽  
Subjective Test ◽  
Medical Image Compression ◽  
Research Issues ◽  
Software And Hardware

The rapid development of medical imaging and the invention of various medicines have benefited mankind and the whole community. Medical image processing is a niche area concerned with the operations and processes of generating images of the human body for clinical purposes.  Potential areas such as image acquisition, image enhancement, image compression and storage, and image based visualization also include in medical image processing analysis. Unfortunately, medical image compression dealing with three-dimensional (3-D) modalities still in the pre-matured stage. Along with that, very limited researchers take a challenge to apply hardware on their implementation. Referring to the previous work reviewed, most of the compression method used lossless rather than lossy. For implementation using software, MATLAB and Verilog are the famous candidates among researchers. In term of analysis, most of the previous works conducted objective test compared with subjective test. This paper thoroughly reviews the recent advances in medical image compression mainly in terms of types of compression, software and hardware implementations and performance evaluation. Furthermore, challenges and open research issues are discussed in order to provide perspectives for future potential research. In conclusion, the overall picture of the image processing landscape, where several researchers more focused on software implementations and various combinations of software and hardware implementation.  

scholarly journals Pipeline architectures of Three-dimensional daubechies wavelet transform using hybrid method

2019 ◽  
Vol 15 (1) ◽  
pp. 240
Author(s):  
Noor Huda Ja’afar ◽  
Afandi Ahmad
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Hybrid Method ◽  
Medical Image ◽  
Three Dimensional ◽  
Building Blocks ◽  
Mapping Technique ◽  
Discrete Wavelet ◽  
Daubechies Wavelet ◽  
Medical Image Compression

<span>The application of three-dimensional (3-D) medical image compression systems uses several building blocks for its computationally intensive algorithms to perform matrix transformation operations. Complexity in addressing large medical volumes data has resulted in vast challenges from a hardware implementation perspective. This paper presents an approach towards very-large-scale-integration (VLSI) implementation of 3-D Daubechies wavelet transform for medical image compression. Discrete wavelet transform (DWT) algorithm is used to design the proposed architectures with pipelined direct mapping technique. Hybrid method use a combination of hardware description language (HDL) and G-code, where this method provides an advantage compared to traditional method. The proposed pipelined architectures are deployed for adaptive transformation process of medical image compression applications. The soft IP core design was targeted on to Xilinx field programmable gate array (FPGA) single board RIO (sbRIO 9632). Results obtained for 3-D DWT architecture using Daubechies 4-tap (Daub4) implementation exhibits promising results in terms of area, power consumption and maximum frequency compared to Daubechies 6-tap (Daub6).</span>

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