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... Show moreOptical 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. Show less
We have studied shape with a particular focus on the zebrafish model system. The shape is an essential appearance of the phenotype of a biological specimen and it can be used to read out a... Show moreWe have studied shape with a particular focus on the zebrafish model system. The shape is an essential appearance of the phenotype of a biological specimen and it can be used to read out a current state or response or to study gene expression. So accurate shape analysis requires a precise shape description. Moreover, a sufficiently large sampling size of the specimens is necessary to ensure a justified and unbiased shape analysis. The latter is very important for high-throughput in compound screening. Therefore, top performance in zebrafish analysis requires high-throughput imaging (HTI). To deal with HTI, we aim to design an elaborate and well-performing HTI architecture. For the essential operations we need computational approaches to obtain the 2D/3D shape representations that are precise and yet can be acquired fast. The quality of the obtained shape descriptions will be validated in a straightforward manner with scalar primitives, i.e., the volume and surface area of a 3D shape. These primitives serve as 3D measurements for a robust primary shape assessment in the phenotype characterisation. Using only shape description is not sufficient, e.g., for high-resolution imaging on tissue and cellular level, so texture should be considered to complement and enhance the shape analysis. Show less
The introductory chapter provides an overview of various aspects related to quantitative analysis of cardiovascular MR (CMR) imaging studies. Subsequently, the thesis describes several automated... Show moreThe introductory chapter provides an overview of various aspects related to quantitative analysis of cardiovascular MR (CMR) imaging studies. Subsequently, the thesis describes several automated methods for quantitative assessment of left ventricular function from CMR imaging studies. Several novel computer algorithms are introduced and validated for automated segmentation of short-axis CMR images and validated by comparing functional results derived from automated segmentation with results derived from manually traced contours. In addition an automated method is presented for assessment of flow through the aorta based on Phase-Contrast flow velocity mapping MRI. Finally a method is presented for accurate assessment of the thickness of the left ventricular myocardium taking advantage of the three-dimensional nature of MRI. Show less
In this thesis we aim at automating the analysis of 3D echocardiography, mainly targeting the functional analysis of the left ventricle. Manual analysis of these data is cumbersome, time-consuming... Show moreIn this thesis we aim at automating the analysis of 3D echocardiography, mainly targeting the functional analysis of the left ventricle. Manual analysis of these data is cumbersome, time-consuming and is associated with inter-observer and inter-institutional variability. Methods for reconstruction of 3D echocardiographic images from fast rotating ultrasound transducers is presented and methods for analysis of 3D echocardiography in general, using tracking, detection and model-based segmentation techniques to ultimately fully automatically segment the left ventricle for functional analysis. We show that reliable quantification of left ventricular volume and mitral valve displacement can be achieved using the presented techniques. Show less
