Computer-aided recognition of dental implants in X-ray images

Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.

Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

Mejoras en el procesamiento de imágenes de TC para el tratamiento con radioterapia adaptativa del cáncer de próstata

El cáncer de próstata es el tipo de cáncer con mayor prevalencia entre los hombres del mundo occidental y, pese a tener una alta tasa de supervivencia relativa, es la segunda mayor causa de muerte por cáncer en este sector de la población. El tratamiento de elección frente al cáncer de próstata es, en la mayoría de los casos, la radioterapia externa. Las técnicas más modernas de radioterapia externa, como la radioterapia modulada en intensidad, permiten incrementar la dosis en el tumor mientras se reduce la dosis en el tejido sano. Sin embargo, la localización del volumen objetivo varía con el día de tratamiento, y se requieren movimientos muy pequeños de los órganos para sacar partes del volumen objetivo fuera de la región terapéutica, o para introducir tejidos sanos críticos dentro. Para evitar esto se han desarrollado técnicas más avanzadas, como la radioterapia guiada por imagen, que se define por un manejo más preciso de los movimientos internos mediante una adaptación de la planificación del tratamiento basada en la información anatómica obtenida de imágenes de tomografía computarizada (TC) previas a la sesión terapéutica. Además, la radioterapia adaptativa añade la información dosimétrica de las fracciones previas a la información anatómica. Uno de los fundamentos de la radioterapia adaptativa es el registro deformable de imágenes, de gran utilidad a la hora de modelar los desplazamientos y deformaciones de los órganos internos. Sin embargo, su utilización conlleva nuevos retos científico-tecnológicos en el procesamiento de imágenes, principalmente asociados a la variabilidad de los órganos, tanto en localización como en apariencia. El objetivo de esta tesis doctoral es mejorar los procesos clínicos de delineación automática de contornos y de cálculo de dosis acumulada para la planificación y monitorización de tratamientos con radioterapia adaptativa, a partir de nuevos métodos de procesamiento de imágenes de TC (1) en presencia de contrastes variables, y (2) cambios de apariencia del recto. Además, se pretende (3) proveer de herramientas para la evaluación de la calidad de los contornos obtenidos en el caso del gross tumor volumen (GTV). Las principales contribuciones de esta tesis doctoral son las siguientes: _ 1. La adaptación, implementación y evaluación de un algoritmo de registro basado en el flujo óptico de la fase de la imagen como herramienta para el cálculo de transformaciones no-rígidas en presencia de cambios de intensidad, y su aplicabilidad a tratamientos de radioterapia adaptativa en cáncer de próstata con uso de agentes de contraste radiológico. Los resultados demuestran que el algoritmo seleccionado presenta mejores resultados cualitativos en presencia de contraste radiológico en la vejiga, y no distorsiona la imagen forzando deformaciones poco realistas. 2. La definición, desarrollo y validación de un nuevo método de enmascaramiento de los contenidos del recto (MER), y la evaluación de su influencia en el procedimiento de radioterapia adaptativa en cáncer de próstata. Las segmentaciones obtenidas mediante el MER para la creación de máscaras homogéneas en las imágenes de sesión permiten mejorar sensiblemente los resultados de los algoritmos de registro en la región rectal. Así, el uso de la metodología propuesta incrementa el índice de volumen solapado entre los contornos manuales y automáticos del recto hasta un valor del 89%, cercano a los resultados obtenidos usando máscaras manuales para el registro de las dos imágenes. De esta manera se pueden corregir tanto el cálculo de los nuevos contornos como el cálculo de la dosis acumulada. 3. La definición de una metodología de evaluación de la calidad de los contornos del GTV, que permite la representación de la distribución espacial del error, adaptándola a volúmenes no-convexos como el formado por la próstata y las vesículas seminales. Dicha metodología de evaluación, basada en un nuevo algoritmo de reconstrucción tridimensional y una nueva métrica de cuantificación, presenta resultados precisos con una gran resolución espacial en un tiempo despreciable frente al tiempo de registro. Esta nueva metodología puede ser una herramienta útil para la comparación de distintos algoritmos de registro deformable orientados a la radioterapia adaptativa en cáncer de próstata. En conclusión, el trabajo realizado en esta tesis doctoral corrobora las hipótesis de investigación postuladas, y pretende servir como cimiento de futuros avances en el procesamiento de imagen médica en los tratamientos de radioterapia adaptativa en cáncer de próstata. Asimismo, se siguen abriendo nuevas líneas de aplicación futura de métodos de procesamiento de imágenes médicas con el fin de mejorar los procesos de radioterapia adaptativa en presencia de cambios de apariencia de los órganos, e incrementar la seguridad del paciente. I.2 Inglés Prostate cancer is the most prevalent cancer amongst men in the Western world and, despite having a relatively high survival rate, is the second leading cause of cancer death in this sector of the population. The treatment of choice against prostate cancer is, in most cases, external beam radiation therapy. The most modern techniques of external radiotherapy, as intensity modulated radiotherapy, allow increasing the dose to the tumor whilst reducing the dose to healthy tissue. However, the location of the target volume varies with the day of treatment, and very small movements of the organs are required to pull out parts of the target volume outside the therapeutic region, or to introduce critical healthy tissues inside. Advanced techniques, such as the image-guided radiotherapy (IGRT), have been developed to avoid this. IGRT is defined by more precise handling of internal movements by adapting treatment planning based on the anatomical information obtained from computed tomography (CT) images prior to the therapy session. Moreover, the adaptive radiotherapy adds dosimetric information of previous fractions to the anatomical information. One of the fundamentals of adaptive radiotherapy is deformable image registration, very useful when modeling the displacements and deformations of the internal organs. However, its use brings new scientific and technological challenges in image processing, mainly associated to the variability of the organs, both in location and appearance. The aim of this thesis is to improve clinical processes of automatic contour delineation and cumulative dose calculation for planning and monitoring of adaptive radiotherapy treatments, based on new methods of CT image processing (1) in the presence of varying contrasts, and (2) rectum appearance changes. It also aims (3) to provide tools for assessing the quality of contours obtained in the case of gross tumor volume (GTV). The main contributions of this PhD thesis are as follows: 1. The adaptation, implementation and evaluation of a registration algorithm based on the optical flow of the image phase as a tool for the calculation of non-rigid transformations in the presence of intensity changes, and its applicability to adaptive radiotherapy treatment in prostate cancer with use of radiological contrast agents. The results demonstrate that the selected algorithm shows better qualitative results in the presence of radiological contrast agents in the urinary bladder, and does not distort the image forcing unrealistic deformations. 2. The definition, development and validation of a new method for masking the contents of the rectum (MER, Spanish acronym), and assessing their impact on the process of adaptive radiotherapy in prostate cancer. The segmentations obtained by the MER for the creation of homogenous masks in the session CT images can improve significantly the results of registration algorithms in the rectal region. Thus, the use of the proposed methodology increases the volume overlap index between manual and automatic contours of the rectum to a value of 89%, close to the results obtained using manual masks for both images. In this way, both the calculation of new contours and the calculation of the accumulated dose can be corrected. 3. The definition of a methodology for assessing the quality of the contours of the GTV, which allows the representation of the spatial distribution of the error, adapting it to non-convex volumes such as that formed by the prostate and seminal vesicles. Said evaluation methodology, based on a new three-dimensional reconstruction algorithm and a new quantification metric, presents accurate results with high spatial resolution in a time negligible compared to the registration time. This new approach may be a useful tool to compare different deformable registration algorithms oriented to adaptive radiotherapy in prostate cancer In conclusion, this PhD thesis corroborates the postulated research hypotheses, and is intended to serve as a foundation for future advances in medical image processing in adaptive radiotherapy treatment in prostate cancer. In addition, it opens new future applications for medical image processing methods aimed at improving the adaptive radiotherapy processes in the presence of organ’s appearance changes, and increase the patient safety.

Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A novel Statistical Shape Model for treatment planning of Retinoblastoma

Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes. Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

An automatic classifier of emotions built from entropy of noise

The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion.

Evidence for divided automatic attention

A long-standing debate in the literature is whether attention can form two or more independent spatial foci in addition to the well-known unique spatial focus. There is evidence that voluntary visual attention divides in space. The possibility that this also occurs for automatic visual attention was investigated here. Thirty-six female volunteers were tested. In each trial, a prime stimulus was presented in the left or right visual hemifield. This stimulus was characterized by the blinking of a superior, middle or inferior ring, the blinking of all these rings, or the blinking of the superior and inferior rings. A target stimulus to which the volunteer should respond with the same side hand or a target stimulus to which she should not respond was presented 100 ms later in a primed location, a location between two primed locations or a location in the contralateral hemifield. Reaction time to the positive target stimulus in a primed location was consistently shorter than reaction time in the horizontally corresponding contralateral location. This attentional effect was significantly smaller or absent when the positive target stimulus appeared in the middle location after the double prime stimulus. These results suggest that automatic visual attention can focus on two separate locations simultaneously, to some extent sparing the region in between.

Characterizing chaotic melodies in automatic music composition

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests. (c) 2010 American Institute of Physics. [doi: 10.1063/1.3487516]

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

SAB(IO): A BIOLOGICALLY PLAUSIBLE CONNECTIONIST APPROACH TO AUTOMATIC TEXT SUMMARIZATION

An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the sa-called biologically implausible algorithms.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.