Registration of Standardized Histological Images in Feature Space

In this paper, we propose three novel and important methods for the registration of histological images for 3D reconstruction. First, possible intensity variations and nonstandardness in images are corrected by an intensity standardization process which maps the image scale into a standard scale where the similar intensities correspond to similar tissues meaning. Second, 2D histological images are mapped into a feature space where continuous variables are used as high confidence image features for accurate registration. Third, we propose an automatic best reference slice selection algorithm that improves reconstruction quality based on both image entropy and mean square error of the registration process. We demonstrate that the choice of reference slice has a significant impact on registration error, standardization, feature space and entropy information. After 2D histological slices are registered through an affine transformation with respect to an automatically chosen reference, the 3D volume is reconstructed by co-registering 2D slices elastically.Comment: SPIE Medical Imaging 2008 - submissio

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

Large Deformation Diffeomorphic Metric Mapping Registration of Reconstructed 3D Histological Section Images and in vivo MR Images

Our current understanding of neuroanatomical abnormalities in neuropsychiatric diseases is based largely on magnetic resonance imaging (MRI) and post mortem histological analyses of the brain. Further advances in elucidating altered brain structure in these human conditions might emerge from combining MRI and histological methods. We propose a multistage method for registering 3D volumes reconstructed from histological sections to corresponding in vivo MRI volumes from the same subjects: (1) manual segmentation of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) compartments in histological sections, (2) alignment of consecutive histological sections using 2D rigid transformation to construct a 3D histological image volume from the aligned sections, (3) registration of reconstructed 3D histological volumes to the corresponding 3D MRI volumes using 3D affine transformation, (4) intensity normalization of images via histogram matching, and (5) registration of the volumes via intensity based large deformation diffeomorphic metric (LDDMM) image matching algorithm. Here we demonstrate the utility of our method in the transfer of cytoarchitectonic information from histological sections to identify regions of interest in MRI scans of nine adult macaque brains for morphometric analyses. LDDMM improved the accuracy of the registration via decreased distances between GM/CSF surfaces after LDDMM (0.39 ± 0.13 mm) compared to distances after affine registration (0.76 ± 0.41 mm). Similarly, WM/GM distances decreased to 0.28 ± 0.16 mm after LDDMM compared to 0.54 ± 0.39 mm after affine registration. The multistage registration method may find broad application for mapping histologically based information, for example, receptor distributions, gene expression, onto MRI volumes

A Multi-Path Approach to Histology Volume Reconstruction

This paper presents a method for correcting erratic pairwise registrations when reconstructing a volume from 2D histology slices. Due to complex and unpredictable alterations of the content of histology images, a pairwise rigid registration between two adjacent slices may fail systematically. Conversely, a neighbouring registration, which potentially involves one of these two slices, will work. This grounds our approach: using correct spatial correspondences established through neighbouring registrations to account for direct failures. We propose to search the best alignment of every couple of adjacent slices from a finite set of transformations that involve neighbouring slices in a transitive fashion. Using the proposed method, we obtained reconstructed volumes with increased coherence compared to the classical pairwise approach, both in synthetic and real data

Tomato protoplast DNA transformation: physical linkage and recombination of exogenous DNA sequences

Tomato protoplasts have been transformed with plasmid DNA's, containing a chimeric kanamycin resistance gene and putative tomato origins of replication. A calcium phosphate-DNA mediated transformation procedure was employed in combination with either polyethylene glycol or polyvinyl alcohol. There were no indications that the tomato DNA inserts conferred autonomous replication on the plasmids. Instead, Southern blot hybridization analysis of seven kanamycin resistant calli revealed the presence of at least one kanamycin resistance locus per transformant integrated in the tomato nuclear DNA. Generally one to three truncated plasmid copies were found integrated into the tomato nuclear DNA, often physically linked to each other. For one transformant we have been able to use the bacterial ampicillin resistance marker of the vector plasmid pUC9 to 'rescue' a recombinant plasmid from the tomato genome. Analysis of the foreign sequences included in the rescued plasmid showed that integration had occurred in a non-repetitive DNA region. Calf-thymus DNA, used as a carrier in transformation procedure, was found to be covalently linked to plasmid DNA sequences in the genomic DNA of one transformant. A model is presented describing the fate of exogenously added DNA during the transformation of a plant cell. The results are discussed in reference to the possibility of isolating DNA sequences responsible for autonomous replication in tomato.

Piecewise Affine Registration of Biological Images for Volume Reconstruction

This manuscript tackles the reconstruction of 3D volumes via mono-modal registration of series of 2D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover’s distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise

Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd–EOB–DTPA-enhanced MRI

Accurate detection of liver lesions is of great importance in hepatic surgery planning. Recent studies have shown that the detection rate of liver lesions is significantly higher in gadoxetic acid-enhanced magnetic resonance imaging (Gd–EOB–DTPA-enhanced MRI) than in contrast-enhanced portal-phase computed tomography (CT); however, the latter remains essential because of its high specificity, good performance in estimating liver volumes and better vessel visibility. To characterize liver lesions using both the above image modalities, we propose a multimodal nonrigid registration framework using organ-focused mutual information (OF-MI). This proposal tries to improve mutual information (MI) based registration by adding spatial information, benefiting from the availability of expert liver segmentation in clinical protocols. The incorporation of an additional information channel containing liver segmentation information was studied. A dataset of real clinical images and simulated images was used in the validation process. A Gd–EOB–DTPA-enhanced MRI simulation framework is presented. To evaluate results, warping index errors were calculated for the simulated data, and landmark-based and surface-based errors were calculated for the real data. An improvement of the registration accuracy for OF-MI as compared with MI was found for both simulated and real datasets. Statistical significance of the difference was tested and confirmed in the simulated dataset (p < 0.01)

Solid state diffusion in the feldspar system

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Geology, 1953.Includes bibliographical references (leaves 81-92).by William Zanville Leavitt.Ph.D