Upper airways segmentation using principal curvatures

Esta tesis propone una nueva técnica para segmentar las vías aéreas superiores. Esta propuesta permite la extracción de estructuras curvilíneas usando curvaturas principales. La propuesta permite la extracción de éstas estructuras en imágenes 2D y 3D. Entre las principales novedades se encuentra la propuesta de un nuevo criterio de parada en la propagación del algoritmo de realce de contraste (operador multi-escala de tipo sombrero alto). De la misma forma, el criterio de parada propuesto es usado para detener los algoritmos de difusión anisotrópica. Además, un nuevo criterio es propuesto para seleccionar las curvaturas principales que conforman las estructuras curvilíneas, que se basa en los criterios propuestos por Steger, Deng et. al. y Armande et. al. Además, se propone un nuevo algoritmo para realizar la supresión de nomáximos que permite reducir la presencia de discontinuidades en el borde de las estructuras curvilíneas. Para extraer los bordes de las estructuras curvilíneas, se utiliza un algoritmo de enlace que incluye un nuevo criterio de distancia para reducir la aparición de agujeros en la estructura final. Finalmente, con base en los resultados obtenidos, se utiliza un algoritmo morfológico para cerrar los agujeros y se aplica un algoritmo de crecimiento de regiones para obtener la segmentación final de las vías respiratorias superiores.This dissertation proposes a new approach to segment the upper airways. This proposal allows the extraction of curvilinear structures based on the principal curvatures. The proposal allows extracting these structures from 2D and 3D images. Among the main novelties is the proposal of a new stopping criterion to stop the propagation of the contrast enhancement algorithm (multiscale top-hat morphological operator). In the same way, the proposed stopping criterion is used to stop the anisotropic diffusion algorithms. In addition, a new criterion is proposed to select the principal curvatures that make up the curvilinear structures, which is based on the criteria proposed by Steger, Deng et. al. and Armande et. al. Furthermore, a new algorithm to perform the non-maximum suppression that allows reducing the presence of discontinuities in the border of curvilinear structures is proposed. To extract the edges of the curvilinear structures, a linking algorithm is used that includes a new distance criterion to reduce the appearance of gaps in the final structure. Finally, based on the obtained results, a morphological algorithm is used to close the gaps and a region growing algorithm to obtain the final upper airways segmentation is applied.Doctor en IngenieríaDoctorad

Image Registration to Map Endoscopic Video to Computed Tomography for Head and Neck Radiotherapy Patients

The purpose of this work was to explore the feasibility of registering endoscopic video to radiotherapy treatment plans for patients with head and neck cancer without physical tracking of the endoscope during the examination. Endoscopy-CT registration would provide a clinical tool that could be used to enhance the treatment planning process and would allow for new methods to study the incidence of radiation-related toxicity. Endoscopic video frames were registered to CT by optimizing virtual endoscope placement to maximize the similarity between the frame and the virtual image. Virtual endoscopic images were rendered using a polygonal mesh created by segmenting the airways of the head and neck with a density threshold. The optical properties of the virtual endoscope were matched to a calibrated model of the real endoscope. A novel registration algorithm was developed that takes advantage of physical constraints on the endoscope to effectively search the airways of the head and neck for the desired virtual endoscope coordinates. This algorithm was tested on rigid phantoms with embedded point markers and protruding bolus material. In these tests, the median registration accuracy was 3.0 mm for point measurements and 3.5 mm for surface measurements. The algorithm was also tested on four endoscopic examinations of three patients, in which it achieved a median registration accuracy of 9.9 mm. The uncertainties caused by the non-rigid anatomy of the head and neck and differences in patient positioning between endoscopic examinations and CT scans were examined by taking repeated measurements after placing the virtual endoscope in surface meshes created from different CT scans. Non-rigid anatomy introduced errors on the order of 1-3 mm. Patient positioning had a larger impact, introducing errors on the order of 3.5-4.5 mm. Endoscopy-CT registration in the head and neck is possible, but large registration errors were found in patients. The uncertainty analyses suggest a lower limit of 3-5 mm. Further development is required to achieve an accuracy suitable for clinical use

Modeling, Simulation, And Visualization Of 3d Lung Dynamics

Medical simulation has facilitated the understanding of complex biological phenomenon through its inherent explanatory power. It is a critical component for planning clinical interventions and analyzing its effect on a human subject. The success of medical simulation is evidenced by the fact that over one third of all medical schools in the United States augment their teaching curricula using patient simulators. Medical simulators present combat medics and emergency providers with video-based descriptions of patient symptoms along with step-by-step instructions on clinical procedures that alleviate the patient\u27s condition. Recent advances in clinical imaging technology have led to an effective medical visualization by coupling medical simulations with patient-specific anatomical models and their physically and physiologically realistic organ deformation. 3D physically-based deformable lung models obtained from a human subject are tools for representing regional lung structure and function analysis. Static imaging techniques such as Magnetic Resonance Imaging (MRI), Chest x-rays, and Computed Tomography (CT) are conventionally used to estimate the extent of pulmonary disease and to establish available courses for clinical intervention. The predictive accuracy and evaluative strength of the static imaging techniques may be augmented by improved computer technologies and graphical rendering techniques that can transform these static images into dynamic representations of subject specific organ deformations. By creating physically based 3D simulation and visualization, 3D deformable models obtained from subject-specific lung images will better represent lung structure and function. Variations in overall lung deformations may indicate tissue pathologies, thus 3D visualization of functioning lungs may also provide a visual tool to current diagnostic methods. The feasibility of medical visualization using static 3D lungs as an effective tool for endotracheal intubation was previously shown using Augmented Reality (AR) based techniques in one of the several research efforts at the Optical Diagnostics and Applications Laboratory (ODALAB). This research effort also shed light on the potential usage of coupling such medical visualization with dynamic 3D lungs. The purpose of this dissertation is to develop 3D deformable lung models, which are developed from subject-specific high resolution CT data and can be visualized using the AR based environment. A review of the literature illustrates that the techniques for modeling real-time 3D lung dynamics can be roughly grouped into two categories: Geometrically-based and Physically-based. Additional classifications would include considering a 3D lung model as either a volumetric or surface model, modeling the lungs as either a single-compartment or a multi-compartment, modeling either the air-blood interaction or the air-blood-tissue interaction, and considering either a normal or pathophysical behavior of lungs. Validating the simulated lung dynamics is a complex problem and has been previously approached by tracking a set of landmarks on the CT images. An area that needs to be explored is the relationship between the choice of the deformation method for the 3D lung dynamics and its visualization framework. Constraints on the choice of the deformation method and the 3D model resolution arise from the visualization framework. Such constraints of our interest are the real-time requirement and the level of interaction required with the 3D lung models. The work presented here discusses a framework that facilitates a physics-based and physiology-based deformation of a single-compartment surface lung model that maintains the frame-rate requirements of the visualization system. The framework presented here is part of several research efforts at ODALab for developing an AR based medical visualization framework. The framework consists of 3 components, (i) modeling the Pressure-Volume (PV) relation, (ii) modeling the lung deformation using a Green\u27s function based deformation operator, and (iii) optimizing the deformation using state-of-art Graphics Processing Units (GPU). The validation of the results obtained in the first two modeling steps is also discussed for normal human subjects. Disease states such as Pneumothorax and lung tumors are modeled using the proposed deformation method. Additionally, a method to synchronize the instantiations of the deformation across a network is also discussed

Segmentation and Deformable Modelling Techniques for a Virtual Reality Surgical Simulator in Hepatic Oncology

Liver surgical resection is one of the most frequently used curative therapies. However, resectability is problematic. There is a need for a computer-assisted surgical planning and simulation system which can accurately and efficiently simulate the liver, vessels and tumours in actual patients. The present project describes the development of these core segmentation and deformable modelling techniques. For precise detection of irregularly shaped areas with indistinct boundaries, the segmentation incorporated active contours - gradient vector flow (GVF) snakes and level sets. To improve efficiency, a chessboard distance transform was used to replace part of the GVF effort. To automatically initialize the liver volume detection process, a rotating template was introduced to locate the starting slice. For shape maintenance during the segmentation process, a simplified object shape learning step was introduced to avoid occasional significant errors. Skeletonization with fuzzy connectedness was used for vessel segmentation. To achieve real-time interactivity, the deformation regime of this system was based on a single-organ mass-spring system (MSS), which introduced an on-the-fly local mesh refinement to raise the deformation accuracy and the mesh control quality. This method was now extended to a multiple soft-tissue constraint system, by supplementing it with an adaptive constraint mesh generation. A mesh quality measure was tailored based on a wide comparison of classic measures. Adjustable feature and parameter settings were thus provided, to make tissues of interest distinct from adjacent structures, keeping the mesh suitable for on-line topological transformation and deformation. More than 20 actual patient CT and 2 magnetic resonance imaging (MRI) liver datasets were tested to evaluate the performance of the segmentation method. Instrument manipulations of probing, grasping, and simple cutting were successfully simulated on deformable constraint liver tissue models. This project was implemented in conjunction with the Division of Surgery, Hammersmith Hospital, London; the preliminary reality effect was judged satisfactory by the consultant hepatic surgeon

Characterising pattern asymmetry in pigmented skin lesions

Abstract. In clinical diagnosis of pigmented skin lesions asymmetric pigmentation is often indicative of melanoma. This paper describes a method and measures for characterizing lesion symmetry. The estimate of mirror symmetry is computed first for a number of axes at different degrees of rotation with respect to the lesion centre. The statistics of these estimates are the used to assess the overall symmetry. The method is applied to three different lesion representations showing the overall pigmentation, the pigmentation pattern, and the pattern of dermal melanin. The best measure is a 100% sensitive and 96% specific indicator of melanoma on a test set of 33 lesions, with a separate training set consisting of 66 lesions

Examination tools for the endoscopic evaluation of the laryngeal adductor reflex

Der gesunde, menschliche Kehlkopf schützt die tieferen Atemwege durch reflexhafte Mechanismen vor dem Eindringen von Partikeln, der sogenannten Aspiration. Einer dieser Mechanismen ist der laryngeale Adduktionsreflex (LAR), der eine rasche Zusammenführung der Stimmlippen bewirkt. Störungen des LAR können zu einer erhöhten Aspirationswahrscheinlichkeit führen – ein Risikofaktor für eine potentiell lebensbedrohliche Lungenentzündung. Ein Routinescreening des LAR bei Verdacht auf einen pathologischen Reflexablauf ist daher medizinisch sinnvoll. Bisherige LAR-Evaluationsverfahren beruhen jedoch auf invasiven, nutzerabhängigen und/oder ungezielten Methoden. Die Reflexperformance wird bislang zudem hauptsächlich qualitativ bewertet. Zur Reduktion der genannten Nachteile wurde an der Medizinischen Hochschule Hannover ein alternatives Verfahren entwickelt und initial erprobt. Dieser Microdroplet Impulse Testing of the LAR (MIT-LAR) genannte Ansatz beruht auf dem Beschuss der Larynxschleimhaut mit einem Tröpfchen. Durch Nutzung eines Hochgeschwindigkeitslaryngoskopsystems und manuelle Auswertung der gewonnenen Bildsequenzen konnte die LAR-Latenz bei Testpersonen mit hoher zeitlicher Auflösung gemessen werden. Obgleich dieses MIT-LAR-System einen Fortschritt gegenüber vorherigen Verfahren darstellt, weist es hinsichtlich der Reproduzierbarkeit der LAR-Auslösung sowie hinsichtlich der Objektivität der optischen LAR-Analyse weiteres Optimierungspotential auf. Sowohl die tropfenvermittelte Stimulation als auch die optische Analyse des LAR werden in der vorliegenden, interdisziplinären Arbeit adressiert: Ein neuartiger Tropfenapplikator ermöglicht die Bildung eines stabilen Stimulationströpfchens mit variabler Mündungsenergie. Eine histologische Analyse des Läsionspotentials an Schweinekehlköpfen ergibt keinen Hinweis auf Gewebeschäden. Zwei stereoskopische Hochgeschwindigkeitslaryngoskope werden konzipiert und aufgebaut. In Kombination mit dem Tropfenapplikator und einem Algorithmus zur Approximation der Tropfenflugbahn ermöglichen diese die Vorhersage des Tropfenaufprallortes. Bei Verwendung eines stablinsen- bzw. bildleiterbasierten Systems werden im Labor Vorhersagefehler von (0,9 ± 0,6) mm bzw. (1,3 ± 0,8) mm gemessen. Abschließend wird ein Verfahren zur automatisierten Analyse von MIT-LAR-Sequenzen entwickelt und an einem Datensatz erprobt. Dies führt zur erstmaligen, computergestützten Messung der Stimmlippen-Winkelgeschwindigkeit während der Adduktionsphase des menschlichen LAR. Im Fall einer vollständigen bzw.~unvollständigen Adduktion werden Werte von (891 ± 516) °/s bzw. (421 ± 221) °/s erhalten. Dies stellt eine Erweiterung des medizinischen Wissensstandes dar.Several reflexive mechanisms in the human larynx protect the deeper respiratory tract from the intrusion of foreign particles, the so-called aspiration. The laryngeal adductor reflex (LAR), which leads to a rapid closure of the glottis, is one of these mechanisms. In consequence, disturbances of the LAR can lead to aspiration – a risk factor for potentially fatal pneumonia. Therefore, a routine screening of the LAR is highly beneficial in cases where a pathological reflex phenotype is suspected. Current LAR evaluation approaches rely on invasive, user-dependent, and/or untargeted methods. Moreover, the reflex performance is currently mainly being assessed qualitatively. To mitigate these disadvantages, an alternative method has recently been developed and initially tested at Hannover Medical School. This method, referred to as Microdroplet Impulse Testing of the LAR (MIT-LAR), is based on impacting the laryngeal mucosa with a droplet. By using a high-speed laryngoscope, combined with a manual analysis of the recorded high-speed sequence showing the reflexive response, the LAR onset latency could be measured at a high temporal resolution. Although the MIT-LAR system represents a technological progress with respect to prior methods, it still offers further potential for development regarding the reproducibility of LAR stimulation and the objectivity of LAR evaluation. Both droplet-based LAR stimulation and optical LAR analysis are in the focus of the present, interdisciplinary work: A novel droplet applicator module enables stabilization of droplet formation and droplet muzzle energy control. A histological analysis of the droplet’s lesion potential on porcine larynges does not yield any sign of tissue damage. Two stereoscopic high-speed laryngoscopes are designed and set up. In combination with the droplet applicator and an algorithm for the approximation of the droplet trajectory, this enables the prediction of the droplet impact site. The prediction error of both laryngoscopic systems is evaluated in a laboratory setting. A value of (0.9 0.6)mm is measured using a rod lens-based system; a fiber-based optics yields a value of (1.3 0.8)mm. Finally, a method for the automatic analysis of MIT-LAR sequences is developed and tested on a data set. This leads to the first computer-assisted measurement of the angular velocity of the vocal folds during the adduction phase of the human LAR. When complete/incomplete adduction is achieved, values of (891 516) ° s−1 and (421 221) ° s−1 are obtained, respectively. This constitutes an expansion of the state of medical knowledg

Medical-Data-Models.org:A collection of freely available forms (September 2016)

MDM-Portal (Medical Data-Models) is a meta-data repository for creating, analysing, sharing and reusing medical forms, developed by the Institute of Medical Informatics, University of Muenster in Germany. Electronic forms for documentation of patient data are an integral part within the workflow of physicians. A huge amount of data is collected either through routine documentation forms (EHRs) for electronic health records or as case report forms (CRFs) for clinical trials. This raises major scientific challenges for health care, since different health information systems are not necessarily compatible with each other and thus information exchange of structured data is hampered. Software vendors provide a variety of individual documentation forms according to their standard contracts, which function as isolated applications. Furthermore, free availability of those forms is rarely the case. Currently less than 5 % of medical forms are freely accessible. Based on this lack of transparency harmonization of data models in health care is extremely cumbersome, thus work and know-how of completed clinical trials and routine documentation in hospitals are hard to be re-used. The MDM-Portal serves as an infrastructure for academic (non-commercial) medical research to contribute a solution to this problem. It already contains more than 4,000 system-independent forms (CDISC ODM Format, www.cdisc.org, Operational Data Model) with more than 380,000 dataelements. This enables researchers to view, discuss, download and export forms in most common technical formats such as PDF, CSV, Excel, SQL, SPSS, R, etc. A growing user community will lead to a growing database of medical forms. In this matter, we would like to encourage all medical researchers to register and add forms and discuss existing forms