Literature DB >> 32355650

Three-dimensional organ extraction method for color volume image based on the closed-form solution strategy.

Bin Liu1,2, Xiaohui Zhang1, Liang Yang3, Jianxin Zhang4,5.   

Abstract

With the rapid development of computer technology, surgical training, and the digitalized teaching of human body morphology are gaining prominence in medical education. Accurate, true organ models are essential digital material for these computer-assisted systems. However, no direct three-dimensional (3D) true organ model acquisition method currently exists. Thus, the direct extraction of the interested organ models based on the existing Virtual Human Project (VHP) image set is urgently needed. In this paper, a closed-form solution-based volume matting method is proposed. Using a small quantity of graffiti in the foreground and background, target 3D regions can be extracted by closed-form solution computing. The upper triangular storage strategy and the preconditioned conjugate-gradient (PCG) method also promote robustness. Four image data sets (2 virtual human male and 2 virtual human female) from the United States National Library of Medicine (including brain slices, eye slices, lung slices, heart slices, liver slices, kidney slices, spine slices, arm slices, vastus slices, and foot slices) were selected to extract the 3D volume organ models. The experimental results show that the extracted 3D organs were acceptable and satisfactory. This method may provide technical support for medical and other scientific research fields. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Virtual Human Project (VHP); closed-form solution; color volume image; image matting

Year:  2020        PMID: 32355650      PMCID: PMC7188608          DOI: 10.21037/qims.2020.03.21

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  5 in total

1.  A closed-form solution to natural image matting.

Authors:  Anat Levin; Dani Lischinski; Yair Weiss
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2008-02       Impact factor: 6.226

2.  Sparse Coding for Alpha Matting.

Authors:  Jubin Johnson; Ehsan Shahrian Varnousfaderani; Hisham Cholakkal; Deepu Rajan
Journal:  IEEE Trans Image Process       Date:  2016-07       Impact factor: 10.856

3.  A Hierarchical Image Matting Model for Blood Vessel Segmentation in Fundus Images.

Authors:  Zhun Fan; Jiewei Lu; Caimin Wei; Han Huang; Xinye Cai; Xinjian Chen
Journal:  IEEE Trans Image Process       Date:  2018-12-17       Impact factor: 10.856

4.  3D Alpha Matting Based Co-segmentation of Tumors on PET-CT Images.

Authors:  Zisha Zhong; Yusung Kim; John Buatti; Xiaodong Wu
Journal:  Mol Imaging Reconstr Anal Mov Body Organs Stroke Imaging Treat (2017)       Date:  2017-09-09

5.  Fully automated segmentation of wrist bones on T2-weighted fat-suppressed MR images in early rheumatoid arthritis.

Authors:  Lun Matthew Wong; Lin Shi; Fan Xiao; James Francis Griffith
Journal:  Quant Imaging Med Surg       Date:  2019-04
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.