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Proceedings Paper

Coherent noise remover for optical projection tomography
Author(s): Liangliang Shi; Di Dong; Yujie Yang; Jun Wang; Alicia Arranz; Jorge Ripoll; Jie Tian
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Paper Abstract

Optical Projection Tomography (OPT) is a 3-Dimentional (3D) imaging technique for small specimens between 1mm and 10mm in size. Due to its high resolution and whole-body imaging ability, OPT has been widely used for imaging of small specimens such as murine embryos, murine organs, zebra fish, and plant sections. During an OPT imaging experiment, the ring artifacts are very common which severely impact the image quality of OPT. A ring artifact is caused by a bad pixel on the camera, or impurities on surface of lens and index matching vessel. Here we term these noises as coherent noise because they stay in the same image region during an OPT experiment. Currently, there is still no effective method to remove coherent noises. To address this problem, we propose a novel method to suppress the coherent noises before 3D OPT reconstruction. Our method consists of two steps: 1) find bad pixel positions on a blank image without specimen by using threshold segmentation, then fix the bad pixels on the projection image by using average of their neighbor pixels, 2) remove remained coherent noises on the sinogram by using Variational Coherent noise Remover (VSNR) method. After the two steps, lots of method can be used to generate the tomographic slices from the modified sinograms. We apply our method to a mouse heart imaging with our home-made OPT system. The experimental results show that our method has a good suppression on coherent noise and greatly improves the image quality. The innovation of our method is that we remove coherent noise automatically from both projection image and sinogram and they complement each other.

Paper Details

Date Published: 17 March 2015
PDF: 6 pages
Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 941723 (17 March 2015); doi: 10.1117/12.2081584
Show Author Affiliations
Liangliang Shi, Institute of Automation (China)
Di Dong, Institute of Automation (China)
Yujie Yang, Institute of Automation (China)
Jun Wang, Harbin Univ. of Science and Technology (China)
Alicia Arranz, ETH Zürich (Sweden)
Jorge Ripoll, Univ. Carlos III de Madrid (Spain)
Jie Tian, Institute of Automation (China)

Published in SPIE Proceedings Vol. 9417:
Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Robert C. Molthen, Editor(s)

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