Statistical methods for analysis and processing of medical ultrasound: applications to segmentation and restoration

In this thesis two major topics inherent with medical ultrasound images are addressed: deconvolution and segmentation. In the first case a deconvolution algorithm is described allowing statistically consistent maximum a posteriori estimates of the tissue reflectivity to be restored. These estimates are proven to provide a reliable source of information for achieving an accurate characterization of biological tissues through the ultrasound echo. The second topic involves the definition of a semi automatic algorithm for myocardium segmentation in 2D echocardiographic images. The results show that the proposed method can reduce inter- and intra observer variability in myocardial contours delineation and is feasible and accurate even on clinical data.

New synthetic strategies to tethered bilayer lipid membranes

Tethered bilayer lipid membranes provide an efficient, stable and versatile platform for the investigation of integrated membrane proteins. However, the incorporation of large proteins, as well as of proteins with a large submembrane part is still a very critical issue and therefore, further optimisation of the system is necessary. The central element of a tBLM is a lipid bilayer. Its proximal leaflet is, at least to some extend, covalently attached to a solid support via a spacer group. The anchor lipid consists of three distinct parts, a lipid headgroup, a spacer group and an anchor. All parts together influence the final bilayer properties. In the frame of this work, the synthesis of new thiolipids for tBLMs on gold has been investigated. The aim was to obtain molecules with longer spacers in order to increase the submembrane space. The systems obtained have been characterized using SPR and EIS. The results obtained during this study are multiple. First, the synthesis of a previously synthesized architecture was successfully scaled up in an industrial lab using a new synthetic approach. The synthesis of large amounts is now feasible. Then, the synthesis of the new thiolipids was carried out taking into account the following requirements: the increase of the submembrane space by having longer ethyleneglycol spacers, the attachment of the molecules to a gold substrate via a thiol bond, and the tunability of the lateral mobility by changing the lipid headgroup. Three different synthetic strategies have been investigated. The polymeric approach did not prove to be successful, merely because of the broad molecular weight distribution. The synthesis of heterofunctionally protected oligoethyleneglycols allowed to obtain ethyleneglycol moieties with 6 and 8 units, but the tedious purification steps gave very low yields. Finally, the block by block synthesis using ethyleneglycol precursors proved to be an efficient and fast method to synthesize the target molecules. Indeed, these were obtained with very high yields, and the separation was very efficient. A whole family of new compounds was obtained, having 6, 8 and 14 ethyleneglycol units and with mono- or diphytanyl lipid headgroups. This new pathway is a very promising synthetic strategy that can be used further in the development of new compounds of the tether system. The formation of bilayers was investigated for the different thiolipids mainly by using EIS. The electrical properties of a bilayer define the quality of the membrane and allow the study of the functionality of proteins embedded in such a system. Despite multiple trials to improve the system using self assembly, Langmuir Blodgett transfer, and detergent mixed vesicles, the new polymer thiolipids did not show as high electrical properties as tBLMs reported in the literature. Nevertheless, it was possible to show that a bilayer could be obtained for the different spacer lengths. These bilayers could be formed using self assembly for the first monolayer, and two different methods for bilayer formation, namely vesicle fusion and solvent exchange. We could furthermore show functional incorporation of the ion carrier valinomycin: the selective transport of K+ ions could be demonstrated. For DPHL, it was even possible to show the functional incorporation of the ion channel gramicidin. The influence of the spacer length is translated into an increase of the spacer capacitance, which could correspond to an increase in the capacity of charge accumulation in the submembrane space. The different systems need to be further optimised to improve the electrical properties of the bilayer. Moreover, the incorporation of larger proteins, and proteins bearing submembrane parts needs to be investigated.

A molecular approach towards tethered bilayer lipid membranes: synthesis and characterization of novel anchor lipids

Tethered bilayer lipid membranes (tBLMs) are a promising model system for the natural cell membrane. They consist of a lipid bilayer that is covalently coupled to a solid support via a spacer group. In this study, we developed a suitable approach to increase the submembrane space in tBLMs. The challenge is to create a membrane with a lower lipid density in order to increase the membrane fluidity, but to avoid defects that might appear due to an increase in the lateral space within the tethered monolayers. Therefore, various synthetic strategies and different monolayer preparation techniques were examined. Synthetical attempts to achieve a large ion reservoir were made in two directions: increasing the spacer length of the tether lipids and increasing the lateral distribution of the lipids in the monolayer. The first resulted in the synthesis of a small library of tether lipids (DPTT, DPHT and DPOT) characterized by 1H and 13C NMR, FD-MS, ATR, DSC and TGA. The synthetic strategy for their preparation includes synthesis of precursor with a double bond anchor that can be easily modified for different substrates (e.g. metal and metaloxide). Here, the double bond was modified into a thiol group suitable for gold surface. Another approach towards the preparation of homogeneous monolayers with decreased two-dimensional packing density was the synthesis of two novel anchor lipids: DPHDL and DDPTT. DPHDL is “self-diluted” tether lipid containing two lipoic anchor moieties. DDPTT has an extended lipophylic part that should lead to the preparation of diluted, leakage free proximal layers that will facilitate the completion of the bilayer. Our tool-box of tether lipids was completed with two fluorescent labeled lipid precursors with respectively one and two phytanyl chains in the hydrophobic region and a dansyl group as a fluorophore. The use of such fluorescently marked lipids is supposed to give additional information for the lipid distribution on the air-water interface. The Langmuir film balance was used to investigate the monolayer properties of four of the synthesized thiolated anchor lipids. The packing density and mixing behaviour were examined. The results have shown that mixing anchor with free lipids can homogeneously dilute the anchor lipid monolayers. Moreover, an increase in the hydrophylicity (PEG chain length) of the anchor lipids leads to a higher packing density. A decrease in the temperature results in a similar trend. However, increasing the number of phytanyl chains per lipid molecule is shown to decrease the packing density. LB-monolayers based on pure and mixed lipids in different ratio and transfer pressure were tested to form tBLMs with diluted inner layers. A combination of the LB-monolayer transfer with the solvent exchange method accomplished successfully the formation of tBLMs based on pure DPOT. Some preliminary investigations of the electrical sealing properties and protein incorporation of self-assembled DPOT and DDPTT-based tBLMs were conducted. The bilayer formation performed by solvent exchange resulted in membranes with high resistances and low capacitances. The appearance of space beneath the membrane is clearly visible in the impedance spectra expressed by a second RC element. The latter brings the conclusion that the longer spacer in DPOT and the bigger lateral space between the DDPTT molecules in the investigated systems essentially influence the electrical parameters of the membrane. Finally, we could show the functional incorporation of the small ion carrier valinomycin in both types of membranes.

Ion channels in mixed tethered bilayer lipid membranes

Mixed tethered bilayer lipid membranes (tBLMs) are described based on the self-assembly of a monolayer on template stripped gold, of an archea analogue thiolipid, 2,3-di-o-phytanyl-sn-glycerol-1-tetraethylene glycol-D,L--lipoic acid ester lipid (DPTL), and a newly designed dilution molecule, tetraethylene glycol-D,L--lipoic acid ester (TEGL). The usage of spacer and addition of extra dilution molecules between the substrate and the bilayer is that this architecture provides an ionic reservoir underneath the membrane, avoiding direct contact of the embedded membrane proteins with the gold electrodes and increasing the lateral diffusion of the bilayer, thus allowing for the incorporation of complex channels proteins which are failed in non-diluted systems. The tBLM is completed by fusion of liposomes made from a mixture of 1,2-diphythanolyl-sn-glycero-3-phosphocholine (DPhyPC), cholesterol, and 1,2-diphytanoyl-sn-Glycero-3-phosphate (DPhyPG) in a molar ratio of 6:3:1. Varying the mixing ratio, the optimum mixing ratio was obtained at a dilution factor of DPTL and TEGL at 90%:10%. Only under these conditions, the mixed tBLM showed electrical properties, as shown by EIS, which are comparable to a BLM. With higher dilution factors, a defect-free lipid bilayer was not formed. Formation of bilayers have been characterized by different techniques, such as surface plasmon resonance (SPR), electrochemical impedance spectroscopy (EIS), atomic force microscopy (AFM), and quartz crystal microbalance (QCM). Different proteins such as hemolysin, melittin, gramicidin, M2, Maxi-K, nAChR and bacteriohodopsin are incorporated into these tBLMs as shown by SPR and EIS studies. Ionic conductivity at 0 V vs. Ag|AgCl, 3M KCl were measured by EIS measurements. Our results indicate that these proteins have been successfully incorporated into a very stable tBLM environment in a functionally active form. Therefore, we conclude that the mixed tBLMs have been successfully designed as a general platform for biosensing and screening purposes of membrane proteins.

Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Myocardial perfusion quantification by means of Contrast-Enhanced Cardiac Magnetic Resonance images relies on time consuming frame-by-frame manual tracing of regions of interest. In this Thesis, a novel automated technique for myocardial segmentation and non-rigid registration as a basis for perfusion quantification is presented. The proposed technique is based on three steps: reference frame selection, myocardial segmentation and non-rigid registration. In the first step, the reference frame in which both endo- and epicardial segmentation will be performed is chosen. Endocardial segmentation is achieved by means of a statistical region-based level-set technique followed by a curvature-based regularization motion. Epicardial segmentation is achieved by means of an edge-based level-set technique followed again by a regularization motion. To take into account the changes in position, size and shape of myocardium throughout the sequence due to out of plane respiratory motion, a non-rigid registration algorithm is required. The proposed non-rigid registration scheme consists in a novel multiscale extension of the normalized cross-correlation algorithm in combination with level-set methods. The myocardium is then divided into standard segments. Contrast enhancement curves are computed measuring the mean pixel intensity of each segment over time, and perfusion indices are extracted from each curve. The overall approach has been tested on synthetic and real datasets. For validation purposes, the sequences have been manually traced by an experienced interpreter, and contrast enhancement curves as well as perfusion indices have been computed. Comparisons between automatically extracted and manually obtained contours and enhancement curves showed high inter-technique agreement. Comparisons of perfusion indices computed using both approaches against quantitative coronary angiography and visual interpretation demonstrated that the two technique have similar diagnostic accuracy. In conclusion, the proposed technique allows fast, automated and accurate measurement of intra-myocardial contrast dynamics, and may thus address the strong clinical need for quantitative evaluation of myocardial perfusion.

Biomimetic bilayer membranes made from polymers and lipids

Amphiphile Blockcopolymere sind in der Lage in Wasser Morphologien auszubilden, die analog sind zur hydrophil-hydrophob-hydrophil-Struktur von natürlichen Lipiddoppelschichten. In dieser Arbeit wird zum ersten Mal die Präparation und Charakterisierung von oberflächengestützten Polymerdoppelschichten aus Polybutadien-b-Polyethylenoxid (PB-PEO) beschrieben. Für die Herstellung dieser Strukturen wurden zwei unterschiedliche Präparationsstrategien verfolgt. Der erste Weg besteht aus einer zweistufigen Methode, bei der im ersten Schritt organisierte Monoschichten mittels Langmuir-Blodgett-Transfer auf Gold übertragen und kovalent angebunden werden. Im zweiten Schritt werden hydrophobe Wechselwirkungen ausgenutzt, um über Langmuir-Schaefer-Transfer eine weitere Schicht aufzubringen. Somit wurden homogene Architekturen erzeugt, die oberflächengestützten Lipiddoppelschichten gleichen. Als alternativer, einstufiger Ansatz zur Herstellung von Polymerdoppelschichten wurde das Spreiten von Polymervesikeln auf Gold verfolgt. Auch hierdurch ließen sich Doppelschichtstrukturen mit einer vollständigen Oberflächenbedeckung erzeugen. Die hergestellten Polymerdoppelschichten besitzen eine Dicke von 11-14 nm, die von der Präparationsmethode abhängt. Die Polymerstrukturen weisen bei Trocknung für 1.5 h eine Stabilität gegenüber Luft auf. Bei längeren Trocknungszeiten von ca. 12 h kommt es zu einer Reorganisation der Oberfläche. Dies deutet darauf hin, dass Wasser dazu notwendig ist die Strukturen auf lange Sicht zu stabilisieren. Um die Biokompatibilität der Polymerschichten nachzuweisen, wurden die Wechselwirkungen mit dem membranaktiven Peptid Polymyxin B und dem Transmembranprotein α-Haemolysin gezeigt. Mobilität ist ein wichtiger Faktor für die korrekte Funktion vieler Transmembranproteine. Um die laterale Diffusionsdynamik innerhalb der künstlichen Strukturen zu untersuchen, wurde die Mobilität eines integralen Modellpeptids und von fluoreszierenden Membransonden gemessen. Es konnte mit einzelmolekülempfindlichen Techniken gezeigt werden, dass das α-helikale Peptid und die kleinen Fluoreszenzfarbstoffe frei im hydrophoben Kern der Polymerdoppelschicht diffundieren können. Die Diffusion von beiden Spezies scheint stark von der Fluidität der Polymermatrix beeinflusst zu sein. Ein weiterer Teil dieser Arbeit widmet sich der Entwicklung eines angemessenen, lipidbasierten Referenzsystems für zukünftige Proteinuntersuchungen. Hierzu wurde eine neue Methode zu Herstellung von peptidgestützten Lipiddoppelschichtmembranen entwickelt. Dies wurde durch kovalente Befestigung eines Thiopeptids an einen Goldfilm und darauffolgende Anbindung eines Lipids erreicht. Zur Ausbildung der Lipiddoppelschicht auf dem Lipopeptidunterbau wurder der Rapid Solvent Exchange verwendet. Die Ausbildung der Lipiddoppelschicht wurde sowohl auf microskopischer als auch auf makroskopischer Ebene nachgewiesen. Im letzten Schritt wurde die Anwendbarkeit des Modelsystems für elektrochemische Messungen durch den funktionalen Einbau des Ionentransporters Valinomycin unter Beweis gestellt.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Pathology hinting as the combination of automatic segmentation with a statistical shape model

With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5 microm were detected, and all drusen at least 93.6 microm high were detected.

Graph-Based Multi-Surface Segmentation of OCT Data Using Trained Hard and Soft Constraints

Optical coherence tomography (OCT) is a well-established image modality in ophthalmology and used daily in the clinic. Automatic evaluation of such datasets requires an accurate segmentation of the retinal cell layers. However, due to the naturally low signal to noise ratio and the resulting bad image quality, this task remains challenging. We propose an automatic graph-based multi-surface segmentation algorithm that internally uses soft constraints to add prior information from a learned model. This improves the accuracy of the segmentation and increase the robustness to noise. Furthermore, we show that the graph size can be greatly reduced by applying a smart segmentation scheme. This allows the segmentation to be computed in seconds instead of minutes, without deteriorating the segmentation accuracy, making it ideal for a clinical setup. An extensive evaluation on 20 OCT datasets of healthy eyes was performed and showed a mean unsigned segmentation error of 3.05 ±0.54 μm over all datasets when compared to the average observer, which is lower than the inter-observer variability. Similar performance was measured for the task of drusen segmentation, demonstrating the usefulness of using soft constraints as a tool to deal with pathologies.

Seeing Spaces: An Eye-Tracking Study Of Speech Segmentation

Speech is often a multimodal process, presented audiovisually through a talking face. One area of speech perception influenced by visual speech is speech segmentation, or the process of breaking a stream of speech into individual words. Mitchel and Weiss (2013) demonstrated that a talking face contains specific cues to word boundaries and that subjects can correctly segment a speech stream when given a silent video of a speaker. The current study expanded upon these results, using an eye tracker to identify highly attended facial features of the audiovisual display used in Mitchel and Weiss (2013). In Experiment 1, subjects were found to spend the most time watching the eyes and mouth, with a trend suggesting that the mouth was viewed more than the eyes. Although subjects displayed significant learning of word boundaries, performance was not correlated with gaze duration on any individual feature, nor was performance correlated with a behavioral measure of autistic-like traits. However, trends suggested that as autistic-like traits increased, gaze duration of the mouth increased and gaze duration of the eyes decreased, similar to significant trends seen in autistic populations (Boratston & Blakemore, 2007). In Experiment 2, the same video was modified so that a black bar covered the eyes or mouth. Both videos elicited learning of word boundaries that was equivalent to that seen in the first experiment. Again, no correlations were found between segmentation performance and SRS scores in either condition. These results, taken with those in Experiment, suggest that neither the eyes nor mouth are critical to speech segmentation and that perhaps more global head movements indicate word boundaries (see Graf, Cosatto, Strom, & Huang, 2002). Future work will elucidate the contribution of individual features relative to global head movements, as well as extend these results to additional types of speech tasks.