International Journal of Advances in Science, Engineering and Technology(IJASEAT)
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Volume-8,Issue-1  ( Jan, 2020 )
Statistics report
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
  Journal Paper

Paper Title
An Automation Segmentation Framework of Building an Anatomical Mouse Model For Bioluminescence Tomography

Bioluminescence tomography is known as a highly ill-posed inverse problem. To improve the reconstruction performance by introducing anatomical structures as a priori knowledge, an automatic segmentation framework has been proposed in this paper to extract the mouse whole-body organs and tissues, which enables to build up a heterogeneous mouse model for reconstruction of bioluminescence tomography. Finally, an in vivo mouse experiment has been conducted to evaluate this framework by using an X-ray computed tomography system and a multi-view bioluminescence imaging system. The findings suggest that the proposed method can realize fast automatic segmentation of mouse anatomical structures, ultimately enhancing the reconstruction performance of bioluminescence tomography. Keywords- Medical image processing, automatic image segmentation, anatomical mouse model, bioluminescence tomography.

Author - Abdullah.M.F.Al-Ali, Abdallah Al-Tahan Al-Nu'aimi

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| Published on 2017-01-30
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