Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.

Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.

Pattern-based segmentation of digital documents: model and implementation

This thesis proposes a new document model, according to which any document can be segmented in some independent components and transformed in a pattern-based projection, that only uses a very small set of objects and composition rules. The point is that such a normalized document expresses the same fundamental information of the original one, in a simple, clear and unambiguous way. The central part of my work consists of discussing that model, investigating how a digital document can be segmented, and how a segmented version can be used to implement advanced tools of conversion. I present seven patterns which are versatile enough to capture the most relevant documents’ structures, and whose minimality and rigour make that implementation possible. The abstract model is then instantiated into an actual markup language, called IML. IML is a general and extensible language, which basically adopts an XHTML syntax, able to capture a posteriori the only content of a digital document. It is compared with other languages and proposals, in order to clarify its role and objectives. Finally, I present some systems built upon these ideas. These applications are evaluated in terms of users’ advantages, workflow improvements and impact over the overall quality of the output. In particular, they cover heterogeneous content management processes: from web editing to collaboration (IsaWiki and WikiFactory), from e-learning (IsaLearning) to professional printing (IsaPress).

Automatic clothes segmentation for soft biometrics

[EN]During the last decade, researchers have verified that clothing can provide information for gender recognition. However, before extracting features, it is necessary to segment the clothing region. We introduce a new clothes segmentation method based on the application of the GrabCut technique over a trixel mesh, obtaining very promising results for a close to real time system. Finally, the clothing features are combined with facial and head context information to outperform previous results in gender recognition with a public database.

Stripe based clothes segmentation

[EN]In this paper, a clothes segmentation method for fashion parsing is described. This method does not rely in a previous pose estimation but people segmentation. Therefore, novel and classic segmentation techniques have been considered and improved in order to achieve accurate people segmentation. Unlike other methods described in the literature, the output is the bounding box and the predominant color of the different clothes and not a pixel level segmentation. The proposal is based on dividing the person area into an initial fixed number of stripes, that are later fused according to similar color distribution. To assess the quality of the proposed method the experiments are carried out with the Fashionista dataset that is widely used in the fashion parsing community.

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.

Über das Vermessen tubulärer Strukturen in der Computertomographie

Die chronisch obstruktive Lungenerkrankung (engl. chronic obstructive pulmonary disease, COPD) ist ein Überbegriff für Erkrankungen, die zu Husten, Auswurf und Dyspnoe (Atemnot) in Ruhe oder Belastung führen - zu diesen werden die chronische Bronchitis und das Lungenemphysem gezählt. Das Fortschreiten der COPD ist eng verknüpft mit der Zunahme des Volumens der Wände kleiner Luftwege (Bronchien). Die hochauflösende Computertomographie (CT) gilt bei der Untersuchung der Morphologie der Lunge als Goldstandard (beste und zuverlässigste Methode in der Diagnostik). Möchte man Bronchien, eine in Annäherung tubuläre Struktur, in CT-Bildern vermessen, so stellt die geringe Größe der Bronchien im Vergleich zum Auflösungsvermögen eines klinischen Computertomographen ein großes Problem dar. In dieser Arbeit wird gezeigt wie aus konventionellen Röntgenaufnahmen CT-Bilder berechnet werden, wo die mathematischen und physikalischen Fehlerquellen im Bildentstehungsprozess liegen und wie man ein CT-System mittels Interpretation als lineares verschiebungsinvariantes System (engl. linear shift invariant systems, LSI System) mathematisch greifbar macht. Basierend auf der linearen Systemtheorie werden Möglichkeiten zur Beschreibung des Auflösungsvermögens bildgebender Verfahren hergeleitet. Es wird gezeigt wie man den Tracheobronchialbaum aus einem CT-Datensatz stabil segmentiert und mittels eines topologieerhaltenden 3-dimensionalen Skelettierungsalgorithmus in eine Skelettdarstellung und anschließend in einen kreisfreien Graphen überführt. Basierend auf der linearen System Theorie wird eine neue, vielversprechende, integral-basierte Methodik (IBM) zum Vermessen kleiner Strukturen in CT-Bildern vorgestellt. Zum Validieren der IBM-Resultate wurden verschiedene Messungen an einem Phantom, bestehend aus 10 unterschiedlichen Silikon Schläuchen, durchgeführt. Mit Hilfe der Skelett- und Graphendarstellung ist ein Vermessen des kompletten segmentierten Tracheobronchialbaums im 3-dimensionalen Raum möglich. Für 8 zweifach gescannte Schweine konnte eine gute Reproduzierbarkeit der IBM-Resultate nachgewiesen werden. In einer weiteren, mit IBM durchgeführten Studie konnte gezeigt werden, dass die durchschnittliche prozentuale Bronchialwandstärke in CT-Datensätzen von 16 Rauchern signifikant höher ist, als in Datensätzen von 15 Nichtrauchern. IBM läßt sich möglicherweise auch für Wanddickenbestimmungen bei Problemstellungen aus anderen Arbeitsgebieten benutzen - kann zumindest als Ideengeber dienen. Ein Artikel mit der Beschreibung der entwickelten Methodik und der damit erzielten Studienergebnisse wurde zur Publikation im Journal IEEE Transactions on Medical Imaging angenommen.

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.

Airway Basal Cell Vascular Endothelial Growth Factor-mediated Cross-Talk Regulates Endothelial Cell Dependent Growth Support of Human Airway Basal Cells

The human airway epithelium is a pseudostratified heterogenous layer comprised of cili-ated, secretory, intermediate and basal cells. As the stem/progenitor population of the airway epi-thelium, airway basal cells differentiate into ciliated and secretory cells to replenish the airway epithelium during physiological turnover and repair. Transcriptome analysis of airway basal cells revealed high expression of vascular endothelial growth factor A (VEGFA), a gene not typically associated with the function of this cell type. Using cultures of primary human airway basal cells, we demonstrate that basal cells express all of the 3 major isoforms of VEGFA (121, 165 and 189) but lack functional expression of the classical VEGFA receptors VEGFR1 and VEGFR2. The VEGFA is actively secreted by basal cells and while it appears to have no direct autocrine function on basal cell growth and proliferation, it functions in a paracrine manner to activate MAPK signaling cascades in endothelium via VEGFR2 dependent signaling pathways. Using a cytokine- and serum-free co-culture system of primary human airway basal cells and human endothelial cells revealed that basal cell secreted VEGFA activated endothelium to ex-press mediators that, in turn, stimulate and support basal cell proliferation and growth. These data demonstrate novel VEGFA mediated cross-talk between airway basal cells and endothe-lium, the purpose of which is to modulate endothelial activation and in turn stimulate and sustain basal cell growth.

Effects and uptake of gold nanoparticles deposited at the air–liquid interface of a human epithelial airway model

The impact of nanoparticles (NPs) in medicine and biology has increased rapidly in recent years. Gold NPs have advantageous properties such as chemical stability, high electron density and affinity to biomolecules, making them very promising candidates as drug carriers and diagnostic tools. However, diverse studies on the toxicity of gold NPs have reported contradictory results. To address this issue, a triple cell co-culture model simulating the alveolar lung epithelium was used and exposed at the air-liquid interface. The cell cultures were exposed to characterized aerosols with 15 nm gold particles (61 ng Au/cm2 and 561 ng Au/cm2 deposition) and incubated for 4 h and 24 h. Experiments were repeated six times. The mRNA induction of pro-inflammatory (TNFalpha, IL-8, iNOS) and oxidative stress markers (HO-1, SOD2) was measured, as well as protein induction of pro- and anti-inflammatory cytokines (IL-1, IL-2, IL-4, IL-6, IL-8, IL-10, GM-CSF, TNFalpha, INFgamma). A pre-stimulation with lipopolysaccharide (LPS) was performed to further study the effects of particles under inflammatory conditions. Particle deposition and particle uptake by cells were analyzed by transmission electron microscopy and design-based stereology. A homogeneous deposition was revealed, and particles were found to enter all cell types. No mRNA induction due to particles was observed for all markers. The cell culture system was sensitive to LPS but gold particles did not cause any synergistic or suppressive effects. With this experimental setup, reflecting the physiological conditions more precisely, no adverse effects from gold NPs were observed. However, chronic studies under in vivo conditions are needed to entirely exclude adverse effects.

MODELING THE DYNAMICS OF AIRWAY CONSTRICTION: EFFECTS OF AGONIST TRANSPORT AND BINDING

Recent advances have revealed that during exogenous airway challenge, airway diameters can not be adequately predicted by their initial diameters. Furthermore, airway diameters can also vary greatly in time on scales shorter than a breath. In order to better understand these phenomena, we developed a multiscale model which allows us to simulate aerosol challenge in the airways during ventilation. The model incorporates agonist-receptor binding kinetics to govern the temporal response of airway smooth muscle (ASM) contraction on individual airway segments, which together with airway wall mechanics, determines local airway caliber. Global agonist transport and deposition is coupled with pressure-driven flow, linking local airway constrictions with global flow dynamics. During the course of challenge, airway constriction alters the flow pattern, redistributing agonist to less constricted regions. This results in a negative feedback which may be a protective property of the normal lung. As a consequence, repetitive challenge can cause spatial constriction patterns to evolve in time, resulting in a loss of predictability of airway diameters. Additionally, the model offers new insight into several phenomena including the intra- and inter-breath dynamics of airway constriction throughout the tree structure.

Awake tracheal intubation using the Sensascope in 13 patients with an anticipated difficult airway

We present the use of the SensaScope, an S-shaped rigid fibreoptic scope with a flexible distal end, in a series of 13 patients at high risk of, or known to have, a difficult intubation. Patients received conscious sedation with midazolam or fentanyl combined with a remifentanil infusion and topical lidocaine to the oral mucosa and to the trachea via a trans-cricoid injection. Spontaneous ventilation was maintained until confirmation of tracheal intubation. In all cases, tracheal intubation was achieved using the SensaScope. The median (IQR [range]) insertion time (measured from the time the facemask was taken away from the face until an end-expiratory CO(2) reading was visible on the monitor) was 58 s (38-111 [28-300]s). In nine of the 13 cases, advancement of the SensaScope into the trachea was easy. Difficulties included a poor view associated with a bleeding diathesis and saliva, transient loss of spontaneous breathing, and difficulty in advancing the tracheal tube in a patient with unforeseen tracheal narrowing. A poor view in two patients was partially improved by a high continuous flow of oxygen. The SensaScope may be a valuable alternative to other rigid or flexible fibreoptic scopes for awake intubation of spontaneously breathing patients with a predicted difficult airway.

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.

Laser scanning microscopy combined with image restoration to analyse a 3D model of the human epithelial airway barrier

A laser scanning microscope collects information from a thin, focal plane and ignores out of focus information. During the past few years it has become the standard imaging method to characterise cellular morphology and structures in static as well as in living samples. Laser scanning microscopy combined with digital image restoration is an excellent tool for analysing the cellular cytoarchitecture, expression of specific proteins and interactions of various cell types, thus defining valid criteria for the optimisation of cell culture models. We have used this tool to establish and evaluate a three dimensional model of the human epithelial airway wall.