| Título: | Automatic Segmentation Framework of Building Anatomical Mouse Model for Bioluminescence Tomography |
| Autores: | Alali, Abdullah; Beihang University |
| Fecha: | 2013-09-01 |
| Publicador: | TELKOMNIKA: Indonesian journal of electrical engineering |
| Fuente: |
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| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | medical image processing; automatic image segmentation; anatomical mouse model |
| Descripción: | 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. |
| Idioma: | Inglés |