3D functional models of monkey brain through elastic registration of histological sections

In this paper we describe a method for the reconstruction and visualization of functional models of monkey brains. Models are built through the registration of high resolution images obtained from the scanning of histological sections with reference photos taken during the brain slicing. From the histological sections it is also possible to acquire specifically activated neuron coordinates introducing functional information in the model. Due to the specific nature of the images (texture information is useless and the sections could be deformed when they were cut and placed on glass) we solved the registration problem by extracting corresponding cerebral cortex borders (extracted with a snake algorithm), and computing from their deformation an image transform modeled as an affine deformation plus a non-linear field evaluated as an elastically constrained deformation minimizing contour distances. Registered images and contours are used then to build 3D models of specific brains by a software tool allowing the interactive visualization of cortical volumes together with the spatially referenced neurons classified and differently colored according to their functionalities

Registration and Analysis of Developmental Image Sequences

Mapping images into the same anatomical coordinate system via image registration is a fundamental step when studying physiological processes, such as brain development. Standard registration methods are applicable when biological structures are mapped to the same anatomy and their appearance remains constant across the images or changes spatially uniformly. However, image sequences of animal or human development often do not follow these assumptions, and thus standard registration methods are unsuited for their analysis. In response, this dissertation tackles the problems of i) registering developmental image sequences with spatially non-uniform appearance change and ii) reconstructing a coherent 3D volume from serially sectioned images with non-matching anatomies between the sections. There are three major contributions presented in this dissertation. First, I develop a similarity metric that incorporates a time-dependent appearance model into the registration framework. The proposed metric allows for longitudinal image registration in the presence of spatially non-uniform appearance change over time—a common medical imaging problem for longitudinal magnetic resonance images of the neonatal brain. Next, a method is introduced for registering longitudinal developmental datasets with missing time points using an appearance atlas built from a population. The proposed method is applied to a longitudinal study of young macaque monkeys with incomplete image sequences. The final contribution is a template-free registration method to reconstruct images of serially sectioned biological samples into a coherent 3D volume. The method is applied to confocal fluorescence microscopy images of serially sectioned embryonic mouse brains.Doctor of Philosoph

Towards Ultra-High Resolution Fibre Tract Mapping of the Human Brain – Registration of Polarised Light Images and Reorientation of Fibre Vectors

Polarised light imaging (PLI) utilises the birefringence of the myelin sheaths in order to visualise the orientation of nerve fibres in microtome sections of adult human post-mortem brains at ultra-high spatial resolution. The preparation of post-mortem brains for PLI involves fixation, freezing and cutting into 100-μm-thick sections. Hence, geometrical distortions of histological sections are inevitable and have to be removed for 3D reconstruction and subsequent fibre tracking. We here present a processing pipeline for 3D reconstruction of these sections using PLI derived multimodal images of post-mortem brains. Blockface images of the brains were obtained during cutting; they serve as reference data for alignment and elimination of distortion artefacts. In addition to the spatial image transformation, fibre orientation vectors were reoriented using the transformation fields, which consider both affine and subsequent non-linear registration. The application of this registration and reorientation approach results in a smooth fibre vector field, which reflects brain morphology. PLI combined with 3D reconstruction and fibre tracking is a powerful tool for human brain mapping. It can also serve as an independent method for evaluating in vivo fibre tractography

Variational Registration of Multiple Images with the SVD based SqN Distance Measure

Image registration, especially the quantification of image similarity, is an important task in image processing. Various approaches for the comparison of two images are discussed in the literature. However, although most of these approaches perform very well in a two image scenario, an extension to a multiple images scenario deserves attention. In this article, we discuss and compare registration methods for multiple images. Our key assumption is, that information about the singular values of a feature matrix of images can be used for alignment. We introduce, discuss and relate three recent approaches from the literature: the Schatten q-norm based SqN distance measure, a rank based approach, and a feature volume based approach. We also present results for typical applications such as dynamic image sequences or stacks of histological sections. Our results indicate that the SqN approach is in fact a suitable distance measure for image registration. Moreover, our examples also indicate that the results obtained by SqN are superior to those obtained by its competitors.Comment: 12 pages, 5 figures, accepted at the conference "Scale Space and Variational Methods" in Hofgeismar, Germany 201

Registration and 3D reconstruction of histological sections: application to mammary gland development

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, mayo de 200

Finite-Difference Time-Domain simulations of transmission microscopy enable a better interpretation of 3D nerve fiber architectures in the brain

In many laboratories, conventional bright-field transmission microscopes are available to study the structure and organization principles of fibrous tissue samples, but they usually provide only 2D information. To access the third (out-of-plane) dimension, more advanced techniques are employed. An example is 3D Polarized Light Imaging (3D-PLI), which measures the birefringence of histological brain sections to derive the spatial nerve fiber orientations. Here, we show how light scattering in transmission microscopy measurements can be leveraged to gain 3D structural information about fibrous tissue samples like brain tissue. For this purpose, we developed a simulation framework using finite-difference time-domain (FDTD) simulations and high performance computing, which can easily be adapted to other microscopy techniques and tissue types with comparable fibrous structures (e.g., muscle fibers, collagen, or artificial fibers). As conventional bright-field transmission microscopy provides usually only 2D information about tissue structures, a three-dimensional reconstruction of fibers across several sections is difficult. By combining our simulations with experimental studies, we show that the polarization-independent transmitted light intensity (transmittance) contains 3D information: We demonstrate in several experimental studies on brain sections from different species (rodent, monkey, human) that the transmittance decreases significantly (by more than 50%) with the increasing out-of-plane angle of the nerve fibers. Our FDTD simulations show that this decrease is mainly caused by polarization-independent light scattering in combination with the finite numerical aperture of the imaging system. This allows to use standard transmission microscopy techniques to obtain 3D information about the fiber inclination and to detect steep fibers, without need for additional measurements.Comment: 33 pages, 19 figure

Cervical weakness and preterm birth: The structure and function of the internal cervical os

The cervix is integral to the maintenance of pregnancy and timely delivery of the baby. Mechanical failure of the cervix resulting in spontaneous preterm birth presents with collapse of the internal os, yet little is known about why the cervix behaves in this way. This may in part be due to research being technically limited and/or limited to punch biopsies of the distal cervix that did not include tissue from the internal os. The aim of this thesis was to re-evaluate cervical anatomy using novel laboratory and imaging methods to gain further insight into the structure of the cervix and how this may influence function during pregnancy. To achieve this, whole cervical samples were obtained from women undergoing hysterectomy for benign pathology. Uterine tissue was subsequently fixed and analysed using 2D and 3D histological methods. Cervical anatomy was characterised using markers for smooth muscle and collagen and analysed using computer-assisted quantification methods. Sequential tissue slices were then reconstructed to produce 3D models of the proximal, middle and distal cervix. High-resolution diffusion-tensor imaging was used to determine whether complex cervical anatomy could be visualised using radiological methods. Tissue was assessed using quantitative and qualitative diffusion methods, and directly compared to immunohistochemically stained tissue. The results obtained demonstrated that diffusion-tensor imaging accurately assessed cervical anatomy and provided further detail in terms of fibre volume, density and organisation. Ex vivo endoscopic ultrasound was used to assess whether current, established medical imaging technology could discern cervical smooth muscle and collagen fibres. Although this method could be used to identify gross anatomical structures, it was not an appropriate method to identify cervical microanatomy. The results described in this thesis provide further insight into how the cervix resists intrauterine forces throughout pregnancy, and then dilates and effaces to allow for delivery of a fetus. Diffusion-tensor imaging accurately assessed cervical anatomy, which may have implications for in vivo characterisation of cervical remodelling during pregnancy and identifying those at risk of delivering early. Finally, observations in this thesis encourage continued re-examination of the cervix using high-resolution imaging to provide insight into function and to develop strategies to discern cervical insufficiency from other known causes of preterm birth