Dissertation

Computational optimisation of optical projection tomography for 3D image analysis

Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale.

Author

Tang, X.

Date

10 June 2020

Links

Thesis in Leiden Repository

Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale. 3D images are computed from a tomogram and therefore OPT is considered as computational imaging. In order to provide imaging and image analysis solutions for large scale biomedical research, optimisation of the OPT reconstruction is required. The aim of the optimisation presented in this thesis includes: (1) accelerate the reconstruction process; (2) reduce the reconstruction artefacts; (3) improve the image quality of 3D image; (4) Find optimal parameters for the iterative reconstruction.Starting from the optimisations that we have elaborated and implemented in the OPT imaging workflow, we have worked on case studies in zebrafish imaging. In this thesis we present one such particular case study (5) as it falls nicely in the order of magnitude for specimens in OPT imaging. The case study is on quantification of tumours in zebrafish and it is explored with image segmentation and object detection using artificial intelligence (AI) techniques.

• 3d image reconstruction
• automated annotation
• centre of rotation correction
• convolutional neural network
• deep learning
• image segmentation
• optical projection tomography
• point spread function
• tumor quantification