Population-wise consistent segmentation of diffusion weighted magnetic resonance images

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 161-167).In this thesis, we investigate unsupervised and semi-supervised methods to construct anatomical atlases and segment medical images. We propose an integrated registration and clustering algorithm to compute an anatomical atlas of fiber-bundles as well as deep gray matter structures from a population of diffusion tensor MR images (DT-MRI). We refer to this algorithm as "Consistency Clustering" since the outputs of the algorithm include population-wise consistent segmentations and correspondence between the subjects. The consistency is ensured through using a single anatomical model for the whole population, which is similar to the atlases used by experts for manual labeling. We experiment with both parametric and non-parametric models for the gray matter and white matter segmentation problems, each model resulting in a different kind of atlas. Consistent population-wise segmentations require development of several integrated algorithms for clustering, registration, atlas-building and outlier rejection. In this thesis we develop, implement and evaluate these tools individually and together as a population-wise segmentation tool. Together, Consistency Clustering enables automatic atlas construction in DT-MRI for a population, either normal or affected by a neural disorder. Consistency Clustering also provides the user the choice to include prior knowledge through a few labeled subjects (semi-supervised) or compute an anatomical atlas in a completely data driven manner (unsupervised). Furthermore, resulting anatomical models are compact representations of populations and can be used for population-wise morphometry. We implement and evaluate these methods using in vivo DT-MRI datasets. We investigate the benefits of population-wise segmentation as opposed to individually segmenting subjects, as well as effects of noise and initialization on the segmentations.by Ulas Ziyan.Ph.D

Nonlinear Dynamics

This volume covers a diverse collection of topics dealing with some of the fundamental concepts and applications embodied in the study of nonlinear dynamics. Each of the 15 chapters contained in this compendium generally fit into one of five topical areas: physics applications, nonlinear oscillators, electrical and mechanical systems, biological and behavioral applications or random processes. The authors of these chapters have contributed a stimulating cross section of new results, which provide a fertile spectrum of ideas that will inspire both seasoned researches and students

New Directions for Contact Integrators

Contact integrators are a family of geometric numerical schemes which guarantee the conservation of the contact structure. In this work we review the construction of both the variational and Hamiltonian versions of these methods. We illustrate some of the advantages of geometric integration in the dissipative setting by focusing on models inspired by recent studies in celestial mechanics and cosmology.Comment: To appear as Chapter 24 in GSI 2021, Springer LNCS 1282

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas

Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis

Super-resolution microscopy provides direct insight into fundamental biological processes occurring at length scales smaller than light’s diffraction limit. The analysis of data at such scales has brought statistical and machine learning methods into the mainstream. Here we provide a survey of data analysis methods starting from an overview of basic statistical techniques underlying the analysis of super-resolution and, more broadly, imaging data. We subsequently break down the analysis of super-resolution data into four problems: the localization problem, the counting problem, the linking problem, and what we’ve termed the interpretation problem

Report / Institute für Physik

The 2014 Report of the Physics Institutes of the Universität Leipzig presents a hopefully interesting overview of our research activities in the past year. It is also testimony of our scientific interaction with colleagues and partners worldwide. We are grateful to our guests for enriching our academic year with their contributions in the colloquium and within the work groups. The open full professorship in the Institute for Experimental Physics I has been filled with an outstanding candidate. We could attract Prof. Ralf Seidel from the University of Münster. He is an expert in molecular biophysics that complements the existing strength in cellular biophysics. Prof. Hollands could fill all positions of his ERC Starting Grant, so that the work on the project \"Quantum Fields and Curvature – Novel Constructive Approach via Operator Product Expansion\" is now running at full pace. Within the Horizon 2020 project LOMID \"Large Cost-effective OLED Microdisplays and their Applications\" (2015-2017) with eight European partners including industry the semiconductor physics group contributes with transparent oxide devices. A joint laboratory for single ion implantation was established between the Leibniz-Institute for Surface Modification (IOM) and the university under the guidance of Profs. Rauschenbach and Meijer. The EU IRSES Network DIONICOS \"Dynamics of and in Complex Systems\", a consortium of 6 European and 12 non-European partners, including sites in England, France and Germany as well as in Russia, Ukraine, India, the United States and Venezuela, started in February 2014. In the next four years the Leipzig node headed by Prof. Janke will profit from the numerous international contacts this network provides. With a joint project, Prof. Kroy and Prof. Cichos participate in the newly established priority research programme SPP 1726 \"Microswimmers\", which started with a kick-off workshop in October 2014. In 2014 the International Graduate College \"Statistical Physics of Complex Systems\" run by the computational physics group has commenced its third 3-years granting period funded by Deutsch-Französische Hochschule (DFH-UFA). Besides the main partner Université de Lorraine in Nancy, France, now also Coventry University, UK, and the Institute for Condensed Matter Physis of the National Academy of Sciences of Ukraine in Lviv, Ukraine, participate as associated partners. During the last week of September the TCO2014 conference \"Transparent Conductive Oxides – Fundamentals and Applications\" took place in honor of the 100th anniversary of the death of Prof. Dr. KarlW. Bädeker. In 1907 Karl Bädeker had discovered transparent conductive materials and oxides in Leipzig. About a hundred participants joined for many invited talks from international experts, intense discussion and new cooperations. At the end of November the by now traditional 15th nternational Workshop on Recent Developments in Computational Physics \"CompPhys14\" organized by Prof. Janke took place in Leipzig. Around 60 scientists from over 10 different countries exchanged ideas and discussed recent progress in several fields of computational physics. Work has successfully continued in the Centers of Excellence (Sonderforschungsbereiche) SFB 762 \"Functionality ofOxide Interfaces\" and SFB TRR 102 \"Polymers under Multiple Constraints: Restricted and Controlled Molecular Order and Mobility\" (just renewed for 2015-2019). Our activities and success are only possible with the generous support fromvarious funding agencies for which we are very grateful and which is individually acknowledged in the brief reports

Advances in planetary geology, volume 1

This publication is a compilation of reports focusing on research into the origin and evolution of the solar system with emphasis on planetary geology

Development of an Atlas-Based Segmentation of Cranial Nerves Using Shape-Aware Discrete Deformable Models for Neurosurgical Planning and Simulation

Twelve pairs of cranial nerves arise from the brain or brainstem and control our sensory functions such as vision, hearing, smell and taste as well as several motor functions to the head and neck including facial expressions and eye movement. Often, these cranial nerves are difficult to detect in MRI data, and thus represent problems in neurosurgery planning and simulation, due to their thin anatomical structure, in the face of low imaging resolution as well as image artifacts. As a result, they may be at risk in neurosurgical procedures around the skull base, which might have dire consequences such as the loss of eyesight or hearing and facial paralysis. Consequently, it is of great importance to clearly delineate cranial nerves in medical images for avoidance in the planning of neurosurgical procedures and for targeting in the treatment of cranial nerve disorders. In this research, we propose to develop a digital atlas methodology that will be used to segment the cranial nerves from patient image data. The atlas will be created from high-resolution MRI data based on a discrete deformable contour model called 1-Simplex mesh. Each of the cranial nerves will be modeled using its centerline and radius information where the centerline is estimated in a semi-automatic approach by finding a shortest path between two user-defined end points. The cranial nerve atlas is then made more robust by integrating a Statistical Shape Model so that the atlas can identify and segment nerves from images characterized by artifacts or low resolution. To the best of our knowledge, no such digital atlas methodology exists for segmenting nerves cranial nerves from MRI data. Therefore, our proposed system has important benefits to the neurosurgical community