Intersubject Regularity in the Intrinsic Shape of Human V1

Previous studies have reported considerable intersubject variability in the three-dimensional geometry of the human primary visual cortex (V1). Here we demonstrate that much of this variability is due to extrinsic geometric features of the cortical folds, and that the intrinsic shape of V1 is similar across individuals. V1 was imaged in ten ex vivo human hemispheres using high-resolution (200 μm) structural magnetic resonance imaging at high field strength (7 T). Manual tracings of the stria of Gennari were used to construct a surface representation, which was computationally flattened into the plane with minimal metric distortion. The instrinsic shape of V1 was determined from the boundary of the planar representation of the stria. An ellipse provided a simple parametric shape model that was a good approximation to the boundary of flattened V1. The aspect ration of the best-fitting ellipse was found to be consistent across subject, with a mean of 1.85 and standard deviation of 0.12. Optimal rigid alignment of size-normalized V1 produced greater overlap than that achieved by previous studies using different registration methods. A shape analysis of published macaque data indicated that the intrinsic shape of macaque V1 is also stereotyped, and similar to the human V1 shape. Previoud measurements of the functional boundary of V1 in human and macaque are in close agreement with these results

Exact Geosedics and Shortest Paths on Polyhedral Surface

We present two algorithms for computing distances along a non-convex polyhedral surface. The first algorithm computes exact minimal-geodesic distances and the second algorithm combines these distances to compute exact shortest-path distances along the surface. Both algorithms have been extended to compute the exact minimalgeodesic paths and shortest paths. These algorithms have been implemented and validated on surfaces for which the correct solutions are known, in order to verify the accuracy and to measure the run-time performance, which is cubic or less for each algorithm. The exact-distance computations carried out by these algorithms are feasible for large-scale surfaces containing tens of thousands of vertices, and are a necessary component of near-isometric surface flattening methods that accurately transform curved manifolds into flat representations.National Institute for Biomedical Imaging and Bioengineering (R01 EB001550

Characterizing Retinotopic Mapping Using Conformal Geometry and Beltrami Coefficient: a Preliminary Study

abstract: Functional magnetic resonance imaging (fMRI) has been widely used to measure the retinotopic organization of early visual cortex in the human brain. Previous studies have identified multiple visual field maps (VFMs) based on statistical analysis of fMRI signals, but the resulting geometry has not been fully characterized with mathematical models. This thesis explores using concepts from computational conformal geometry to create a custom software framework for examining and generating quantitative mathematical models for characterizing the geometry of early visual areas in the human brain. The software framework includes a graphical user interface built on top of a selected core conformal flattening algorithm and various software tools compiled specifically for processing and examining retinotopic data. Three conformal flattening algorithms were implemented and evaluated for speed and how well they preserve the conformal metric. All three algorithms performed well in preserving the conformal metric but the speed and stability of the algorithms varied. The software framework performed correctly on actual retinotopic data collected using the standard travelling-wave experiment. Preliminary analysis of the Beltrami coefficient for the early data set shows that selected regions of V1 that contain reasonably smooth eccentricity and polar angle gradients do show significant local conformality, warranting further investigation of this approach for analysis of early and higher visual cortex.Dissertation/ThesisM.S. Computer Science 201

Imaging Informatics and the Human Brain Project: the Role of Structure, Review

(no abstract

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Evaluating Spatial Normalization Methods for the Human Brain

Cortical stimulation mapping (CSM) studies have shown cortical locations for language function are highly variable from one subject to the next. Because no two cortical surfaces are alike and language is a higher order cognitive function, observed variability is attributable to a combination of functional and anatomical variation. If individual variation can be normalized, patterns of language organization may emerge that were heretofore hidden. In order to discover whether or not such patterns exist, computer-aided spatial normalization is required. Because CSM data has been collected on the cortical surface, we believe that a surface-based normalization method will provide more accurate results than will a volume-based method. To investigate this hypothesis, we evaluate a surface-based (Caret) and volume-based method (SPM2). For our application, the "ideal" method would i) minimize variation as measured by spread reduction between cortical language sites across subjects while also ii) preserving anatomical localization of sites. Evaluation technique: Eleven MR image volumes and corresponding CSM site coordinates were selected. Images were segmented to create left hemisphere surface reconstruction for each patient. Individual surfaces were registered to the colin27 human brain atlas using each method. Deformation parameters from each method were applied to CSM coordinates to obtain post-normalization coordinates in 2D space and 3D ICBM152 space. Accuracy metrics were calculated i) as mean distance between language sites across subjects in both 2D and 3D space and ii) by visual inspection of post-normalization site locations on a 2D map. Results: Globally, we found no statistically significant difference between CARET (surface-based method) and SPM2 (volume-based method) as measured by both spread reduction and anatomical localization. Local analysis showed that more than twenty percent of total mapping errors were mapped incorrectly by both methods. There was a statistically significant difference between Caret and SPM2 mapping of type 2 errors

Biomechanical Behavior of a Variable Angle Locked Tibiotalocalcaneal Construct

This paper examines the mechanics of the tibiotalocalcaneal construct made with a PHILOS plating system. A failed device consisting of the LCP plate and cortical, locking, and cannulated screws was used to perform the analysis. Visual, microstructure, and fractographic examinations were carried out to characterize the fracture surface topology. These examinations revealed the presence of surface scratching, inclusions, discoloration, corrosion pits, beach marks, and cleavage and striations on the fracture surface. Further examination of the material crystallography and texture revealed an interaction of S, Ni, and Mo-based inclusions that may have raised pitting susceptibility of the device made with Stainless Steel 316L. These features suggest that the device underwent damage by pitting the corrosion-fatigue mechanism and overloading towards the end to fail the plate and screws in two or more components. The screws failed via conjoint bending and torsion fatigue mechanisms. Computer simulations of variable angle locking screws were performed in this paper. The material of construction of the device was governed by ASTM F138-8 or its ISO equivalent 5832 and exhibited inconsistencies in chemistry and hardness requirements. The failure conditions were matched in finite element modeling and those boundary conditions discussed in this paper