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

Yuxuan HOU; Zhong REN; Yubo TAO; Wei CHEN

doi:10.1631/FITEE.2000234

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

Regular Papers | Updated：2022-05-19

- Learning-based parameter prediction for quality control in three-dimensional medical image compression
- 基于学习方法的三维医学图像压缩质量控制参数预测
- Frontiers of Information Technology & Electronic Engineering Vol. 22, Issue 9, Pages: 1169-1178(2021)
- Affiliations：
  
  State Key Lab of CAD & CG, Zhejiang University, Hangzhou 310058, China
  The First Affiliated Hospital, Zhejiang University, Hangzhou 310003, China
- Author bio：
  
  [ "Yuxuan HOU, E-mail: 3140104190@zju.edu.cn" ]
  Zhong REN, E-mail: renzhong@cad.zju.edu.cn
- Funds：
- DOI：10.1631/FITEE.2000234
  CLC： TP391
- Received：16 May 2020，
  
  Revised：2021-;8-24，
  
  Published：2021-09
- Accepted：
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Yuxuan HOU, Zhong REN, Yubo TAO, et al. Learning-based parameter prediction for quality control in three-dimensional medical image compression[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(9): 1169-1178.
DOI：

Yuxuan HOU, Zhong REN, Yubo TAO, et al. Learning-based parameter prediction for quality control in three-dimensional medical image compression[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(9): 1169-1178. DOI： 10.1631/FITEE.2000234.

摘要

质量控制是三维医学图像压缩过程至关重要的环节，需设定最佳图像压缩参数才能满足特定的压缩质量需求。高效视频编码（HEVC）是目前最先进的压缩工具。其中，量化参数（QP）对HEVC的压缩质量控制起决定性作用，如能对其精确预测，就能完成质量控制的目标；然而，直接将视频压缩领域中的预测方法套用到三维医学数据压缩，精度和效率无法取得令人满意的结果。为此，提出一种基于学习的参数预测方法，用于实现三维医学图像压缩中的高效质量控制。本文方法基于支撑向量回归（SVR），可以直接利用从原始数据中提取的基于视频的特征与基于结构的特征来预测最佳QP，无需经过耗时长的预编码或迭代过程。在若干数据集上的实验结果证明，本文方法比现有方法在预测准确度和速度上表现更好。

Abstract

Quality control is of vital importance in compressing three-dimensional (3D) medical imaging data. Optimal compression parameters need to be determined based on the specific quality requirement. In high efficiency video coding (HEVC)

regarded as the state-of-the-art compression tool

the quantization parameter (QP) plays a dominant role in controlling quality. The direct application of a video-based scheme in predicting the ideal parameters for 3D medical image compression cannot guarantee satisfactory results. In this paper we propose a learning-based parameter prediction scheme to achieve efficient quality control. Its kernel is a support vector regression (SVR) based learning model that is capable of predicting the optimal QP from both video-based and structural image features extracted directly from raw data

avoiding time-consuming processes such as pre-encoding and iteration

which are often needed in existing techniques. Experimental results on several datasets verify that our approach outperforms current video-based quality control methods.

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references

K Clark , , , B Vendt , , , K Smith , , , 等 . . The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository . . J Dig Imag , , 2013 . . 26 ( ( 6 ): ): 1045 - - 1057 . . DOI: 10.1007/s10278-013-9622-7 http://doi.org/10.1007/s10278-013-9622-7 . .

KQ Dinh , , , J Lee , , , J Kim , , , 等 . . Only-reference video quality assessment for video coding using convolutional neural network . . Proc 25 th IEEE Int Conf on Image Processing , , 2018 . . p.2496 - - 2500 . . DOI: 10.1109/ICIP.2018.8451262 http://doi.org/10.1109/ICIP.2018.8451262 . .

I El-Naqa , , , YY Yang , , , NP Galatsanos , , , 等 . . A similarity learning approach to content-based image retrieval: application to digital mammography . . IEEE Trans Med Imag , , 2004 . . 23 ( ( 10 ): ): 1233 - - 1244 . . DOI: 10.1109/TMI.2004.834601 http://doi.org/10.1109/TMI.2004.834601 . .

RM Haralick , , , K Shanmugam , , , IH Dinstein . . Textural features for image classification . . IEEE Trans Syst Man Cybern , , 1973 . . 3 ( ( 6 ): ): 610 - - 621 . . DOI: 10.1109/TSMC.1973.4309314 http://doi.org/10.1109/TSMC.1973.4309314 . .

Q Huynh-Thu , , , M Ghanbari . . Scope of validity of PSNR in image/video quality assessment . . Electron Lett , , 2008 . . 44 ( ( 13 ): ): 800 - - 801 . . DOI: 10.1049/el:20080522 http://doi.org/10.1049/el:20080522 . .

N Kamaci , , , Y Altunbasak , , , RM.264/AVC video coder via Cauchy-density-based rate and distortion models Mersereau . . Frame bit allocation for the H . . IEEE Trans Circ Syst Video Technol , , 2005 . . 15 ( ( 8 ): ): 994 - - 1006 . . DOI: 10.1109/TCSVT.2005.852400 http://doi.org/10.1109/TCSVT.2005.852400 . .

DK Kwon , , , MY Shen , , , CCJ Kuo . . Rate control for H.264 video with enhanced rate and distortion models . . IEEE Trans Circ Syst Video Technol , , 2007 . . 17 ( ( 5 ): ): 517 - - 529 . . DOI: 10.1109/TCSVT.2007.894053 http://doi.org/10.1109/TCSVT.2007.894053 . .

B Lazzerini , , , F Marcelloni , , , M Vecchio . . A multi-objective evolutionary approach to image quality/compression trade-off in JPEG baseline algorithm . . Appl Soft Comput , , 2010 . . 10 ( ( 2 ): ): 548 - - 561 . . DOI: 10.1016/j.asoc.2009.08.024 http://doi.org/10.1016/j.asoc.2009.08.024 . .

F Liu , , , M Hernandez-Cabronero , , , V Sanchez , , , 等 . . The current role of image compression standards in medical imaging . . Information , , 2017 . . 8 ( ( 4 ): ): 131 DOI: 10.3390/info8040131 http://doi.org/10.3390/info8040131 . .

S Ma , , , W Gao , , , Y Lu . . Rate-distortion analysis for H.264/AVC video coding and its application to rate control . . IEEE Trans Circ Syst Video Technol , , 2005 . . 15 ( ( 12 ): ): 1533 - - 1544 . . DOI: 10.1109/TCSVT.2005.857300 http://doi.org/10.1109/TCSVT.2005.857300 . .

SW Ma , , , JJ Si , , , SS Wang . . A study on the rate distortion modeling for high efficiency video coding . . Proc 19 th IEEE Int Conf on Image Processing , , 2012 . . p.181 - - 184 . . DOI: 10.1109/ICIP.2012.6466825 http://doi.org/10.1109/ICIP.2012.6466825 . .

SG Miaou , , , ST Chen . . Automatic quality control for wavelet-based compression of volumetric medical images using distortion-constrained adaptive vector quantization . . IEEE Trans Med Imag , , 2004 . . 23 ( ( 11 ): ): 1417 - - 1429 . . DOI: 10.1109/TMI.2004.835312 http://doi.org/10.1109/TMI.2004.835312 . .

X Pan , , , ZZ Chen . . Multi-layer quantization control for quality-constrained H.265/HEVC . . IEEE Trans Image Process , , 2016 . . 26 ( ( 7 ): ): 3437 - - 3448 . . DOI: 10.1109/TIP.2016.2627818 http://doi.org/10.1109/TIP.2016.2627818 . .

A Patait , , , E Young . . High performance video encoding with NVIDIA GPUs . . GPU Technology Conf , , 2016 . . https://goo.gl/Bdjdgm https://goo.gl/Bdjdgm , , . .

WK Pratt , , , J Kane , , , HC Andrews . . Hadamard transform image coding . . Proc IEEE , , 1969 . . 57 ( ( 1 ): ): 58 - - 68 . . DOI: 10.1109/PROC.1969.6869 http://doi.org/10.1109/PROC.1969.6869 . .

A Said , , , WA Pearlman . . A new, fast, and efficient image codec based on set partitioning in hierarchical trees . . IEEE Trans Circ Syst Video Technol , , 1996 . . 6 ( ( 3 ): ): 243 - - 250 . . DOI: 10.1109/76.499834 http://doi.org/10.1109/76.499834 . .

V Sanchez , , , J Bartrina-Rapesta . . Lossless compression of medical images based on HEVC intra coding . . IEEE Int Conf on Acoustics, Speech and Signal Processing , , 2014 . . p.6622 - - 6626 . . DOI: 10.1109/ICASSP.2014.6854881 http://doi.org/10.1109/ICASSP.2014.6854881 . .

M Santamaria , , , E Izquierdo , , , S Blasi , , , 等 . . Estimation of rate control parameters for video coding using CNN . . IEEE Visual Communications and Image Processing , , 2018 . . p.1 - - 4 . . DOI: 10.1109/VCIP.2018.8698721 http://doi.org/10.1109/VCIP.2018.8698721 . .

B Schlkopf , , , AJ Smola , , , RC Williamson , , , 等 . . New support vector algorithms . . Neur Comput , , 2000 . . 12 ( ( 5 ): ): 1207 - - 1245 . . DOI: 10.1162/089976600300015565 http://doi.org/10.1162/089976600300015565 . .

HL Wang , , , S Kwong . . Rate-distortion optimization of rate control for H.264 with adaptive initial quantization parameter determination . . IEEE Trans Circ Syst Video Technol , , 2008 . . 18 ( ( 1 ): ): 140 - - 144 . . DOI: 10.1109/TCSVT.2007.913757 http://doi.org/10.1109/TCSVT.2007.913757 . .

SJ Wang , , , RM Summers . . Machine learning and radiology . . Med Image Anal , , 2012 . . 16 ( ( 5 ): ): 933 - - 951 . . DOI: 10.1016/j.media.2012.02.005 http://doi.org/10.1016/j.media.2012.02.005 . .

CY Wu , , , PC Su . . A content-adaptive distortion- quantization model for H.264/AVC and its applications . . IEEE Trans Circ Syst Video Technol , , 2013 . . 24 ( ( 1 ): ): 113 - - 126 . . DOI: 10.1109/TCSVT.2013.2273656 http://doi.org/10.1109/TCSVT.2013.2273656 . .

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