Silhouette-based 3D model for zebrafish high-throughput imaging

Good estimations of volume and surface area are important to biological systems measurement. In this paper we develop a 3D reconstruction from evenly sampled axial views in order to enable the volume and surface area measurement. We develop this system for high throughput applications with the zebrafish model system. The VAST BioImager is specifically developed for this purpose and with this system the axial views can be produced. Silhouettes derived from the axial sequence are shape priors which can be directly used to solve the camera calibration problem that is required for the accurate 3D reconstruction. Nonlinear optimisation algorithms have shown to be suitable for the further development of the reconstruction problem. The method proposed in this paper can be included in a measurement pipeline that is used in all kinds of high throughput applications in the zebrafish field. From the 3D reconstruction features can be derived that will contribute to the phenotyping of zebrafish.

[1]  Mehmet Fatih Yanik,et al.  High-throughput in vivo vertebrate screening , 2010, Nature Methods.

[2]  Adrian G. Bors,et al.  3D modeling of multiple-object scenes from sets of images , 2014, Pattern Recognit..

[3]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Richard Szeliski,et al.  Rapid octree construction from image sequences , 1993 .

[5]  Daniel Cremers,et al.  Continuous Global Optimization in Multiview 3D Reconstruction , 2007, EMMCVPR.

[6]  A. Laurentini,et al.  The Visual Hull Concept for Silhouette-Based Image Understanding , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Kiriakos N. Kutulakos,et al.  A Theory of Shape by Space Carving , 2000, International Journal of Computer Vision.

[8]  Wouter J. Veneman,et al.  Establishment and Optimization of a High Throughput Setup to Study Staphylococcus epidermidis and Mycobacterium marinum Infection as a Model for Drug Discovery , 2014, Journal of visualized experiments : JoVE.

[9]  Roberto Cipolla,et al.  Reconstruction in the Round Using Photometric Normals and Silhouettes. , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[10]  Roberto Cipolla,et al.  Silhouette Coherence for Camera Calibration under Circular Motion , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Francis Schmitt,et al.  Silhouette and stereo fusion for 3D object modeling , 2003, Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. 3DIM 2003. Proceedings..

[12]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[13]  Jake K. Aggarwal,et al.  TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2008 .

[14]  L.-K. Shark,et al.  Medical Image Segmentation Using New Hybrid Level-Set Method , 2008, 2008 Fifth International Conference BioMedical Visualization: Information Visualization in Medical and Biomedical Informatics.

[15]  Jean Ponce,et al.  Projective Visual Hulls , 2007, International Journal of Computer Vision.

[16]  Fons J. Verbeek,et al.  Modeling Innate Immune Response to Early Mycobacterium Infection , 2012, Comput. Math. Methods Medicine.

[17]  Jean Ponce,et al.  Carved Visual Hulls for Image-Based Modeling , 2006, International Journal of Computer Vision.

[18]  Fons J. Verbeek,et al.  Pattern Recognition for High Throughput Zebrafish Imaging Using Genetic Algorithm Optimization , 2010, PRIB.

[19]  Daniel Cremers,et al.  Robust Variational Segmentation of 3D Objects from Multiple Views , 2006, DAGM-Symposium.

[20]  Edmond Boyer,et al.  Exact polyhedral visual hulls , 2003, BMVC.

[21]  Hans-Peter Seidel,et al.  A Silhouette-Based Algorithm for Texture Registration and Stitching , 2001, Graph. Model..

[22]  Jeffrey C. Lagarias,et al.  Convergence Properties of the Nelder-Mead Simplex Method in Low Dimensions , 1998, SIAM J. Optim..