Fast and accurate computation of the Euclidean distance transform in medical imaging analysis software

Se implementó una aplicación utilizando el lenguaje de programación Phyton y las librerías ITK y VTK para un cálculo rápido y preciso de la transformada Euclidiana de distancia. Se compararon dos algoritmos, el propuesto por Saitho y el algoritmo de Danielsson en la versión four-points Sequencial Euclidean distance (4SED). Se evaluó la precisión y la velocidad computacional de ambos algoritmos, encontrando que la versión propuesta por Saitho es más rápida. Se implementó una aplicación de software para el cálculo de la transformada Euclidiana de distancia, incluyendo herramientas para la segmentacion de imágenes de micro-CT de estructuras óseas. A futuro esta aplicación puede ser usada en conjunto con otros software para análisis de imágenes en el procesamiento de estructuras oseasFast and accurate computation of the Euclidean distance map transformation is presented using the python programming language in conjunction with the vtk and itk toolkits. Two algorithms are compared on the basis of their efficiency and computational speed; Saitho algorithm and Danielsson’s four-points Sequential Euclidean Distance (4SED). An algorithm is used to compute a scalar distance map from a 3D data set or volume, which can be used to extract specific distance values. The performance time for the Saitho computation speed was less than the Danielsson’s 4SED computation allowing a faster calculation of the Euclidean distance map. A software analysis application was implemented using the Saitho algorithm for the computation of the scalar distance maps; it also included an underlying segmentation method to allow the computation of Euclidean distance maps on micro-CT images of segmented bone structures. In the future, this application could be used in conjunction with other image processing software applications of bone analysi

Super-Resolution for Computed Tomography Based on Discrete Tomography

In computed tomography (CT), partial volume effects impede accurate segmentation of structures that are small with respect to the pixel size. In this paper, it is shown that for objects consisting of a small number of homogen

Computer image registration techniques applied to nuclear medicine images

Modern medicine has been using imaging as a fundamental tool in a wide range of applications. Consequently, the interest in automated registration of images from either the same or different modalities has increased. In this chapter, computer techniques of image registration are reviewed, and cover both their classification and the main steps involved. Moreover, the more common geometrical transforms, optimization and interpolation algorithms are described and discussed. The clinical applications examined emphases nuclear medicine

Super-Resolution Registration Using Tissue-Classified Distance Fields

TRANSACTIONS ON MEDICAL IMAGING, VOL., NO., DATE 2 We present a method for registering the position and orientation of bones across multiple computed-tomography (CT) volumes of the same subject. The method is subvoxel accurate, can operate on multiple bones within a set of volumes, and registers bones that have features commensurate in size to the voxel dimension. First, a geometric object model is extracted from a reference volume image. We use then unsupervised tissue classification to generate from each volume to be registered a super-resolution distance field – a scalar field that specifies, at each point, the signed distance from the point to a material boundary. The distance fields and the geometric bone model are finally used to register an object through the sequence of CT images. In the case of multi-object structures, we infer a motion-directed hierarchy from the distance-field information that allows us to register objects that are not within each other’s capture region. We describe a validation framework and evaluate the new technique in contrast with grey-value registration. Results on human wrist data show average accuracy improvements of 74 % over grey-value registration. The method is of interest to any intra-subject, same-modality registration applications where subvoxel accuracy is desired

A Dynamic-Image Computational Approach for Modeling the Spine

We propose a dynamic-image driven computational approach for the modeling and simulation of the spine. We use static and dynamic medical images, computational methods and anatomic knowledge to accurately model and measure the subject-specific dynamic behavior of structures in the spine. The resulting models have applications in biomechanical simulations, computer animation, and orthopaedic surgery. We first develop a semi-automated motion reconstruction method for measuring 3D motion with sub-millimeter accuracy. The automation of the method enables the study of subject-specific spine kinematics over large groups of population. The accuracy of the method enables the modeling and analysis of small anatomical features that are difficult to capture in-vivo using existing imaging techniques. We then develop a set of computational tools to model spine soft-tissue structures. We build dynamic-motion driven geometric models that combine the complementary strengths of the accurate but static models used in orthopaedics and the dynamic but low level-of-detail multibody simulations used in humanoid computer animation. Leveraging dynamic images and reconstructed motion, this approach allows the modeling and analysis anatomical features that are too small to be imaged in-vivo and of their dynamic behavior. Finally, we generate predictive, subject-specific models of healthy and symptomatic spines. The predictive models help to identify, understand and validate hypotheses about spine disorders

The Effect of Loading, Plantar Ligament Disruption and Surgical Repair on Canine Tarsal Bone Kinematics

Our desire to describe the complex kinematic patterns found in nature often exceeds our ability to record, quantify and characterise them. Constantly faced with technological limitations, investigators may attempt to develop new techniques or reduce the complex motions to more simplified models. Perhaps due to technical limitations, the canine pes is commonly considered as a rigid structure, when in reality, this limb segment is comprised of multiple bones and ligaments and motion can readily be demonstrated during palpation. Despite the potentially important role that tarsal bone kinematics may play in energy conservation mechanisms and pathogenesis of injury or disease, there are no descriptions of normal canine tarsal kinematics during locomotion. A radiolucent cadaveric limb loading device was developed and used in conjunction with a computed tomography based kinematic measurement technique to produce the first description of canine tarsal bone kinematics in three dimensions. Tarsal bones were shown to undergo a complex, yet coordinated patterns of motion that facilitate dorsiflexion of the pes in the normal animal. The same technique was applied to specimens following sequential transection of the plantar ligament and revealed the roles of the various components of this ligament. Complete luxation of the proximal intertarsal joint occurred only after transection of the entire ligament, resulting in an inability to transmit force through this limb segment. The final chapter of this thesis, evaluated the ability of a laterally applied bone plate to re-establish force transmission through this limb segment, providing important information that may help to resolve the open question of what the most appropriate surgical repair technique is in these clinical cases