Image enhancement in digital X-ray angiography

Anyone who does not look back to the beginning throughout a course of action, does not look forward to the end. Hence it necessarily follows that an intention which looks ahead, depends on a recollection which looks back. | Aurelius Augustinus, De civitate Dei, VII.7 (417 A.D.) Chapter 1 Introduction and Summary D espite the development of imaging techniques based on alternative physical phenomena, such as nuclear magnetic resonance, emission of single photons ( -radiation) by radio-pharmaceuticals and photon pairs by electron-positron annihilations, re ection of ultrasonic waves, and the Doppler eect, X-ray based im- age acquisition is still daily practice in medicine. Perhaps this can be attributed to the fact that, contrary to many other phenomena, X-rays lend themselves naturally for registration by means of materials and methods widely available at the time of their discovery | a fact that gave X-ray based medical imaging an at least 50-year head start over possible alternatives. Immediately after the preliminary communica- tion on the discovery of the \new light" by R¨ ontgen [317], late December 1895, the possible applications of X-rays were investigated intensively. In 1896 alone, almost one 1,000 articles about the new phenomenon appeared in print (Glasser [119] lists all of them). Although most of the basics of the diagnostic as well as the therapeutic uses of X-rays had been worked out by the end of that year [289], research on im- proved acquisition and reduction of potential risks for humans continued steadily in the century to follow. The development of improved X-ray tubes, rapid lm changers, image intensiers, the introduction of television cameras into uoroscopy, and com- puters in digital radiography and computerized tomography, formed a succession of achievements which increased the diagnostic potential of X-ray based imaging. One of the areas in medical imaging where X-rays have always played an im- portant role is angiography,y which concerns the visualization of blood vessels in the human body. As already suggested, research on the possibility of visualization of the human vasculature was initiated shortly after the discovery of X-rays. A photograph of a rst \angiogram" | obtained by injection of a mixture of chalk, red mercury, and petroleum into an amputated hand, followed by almost an hour of exposure to X-rays | was published as early as January 1896, by Hascheck & Lindenthal [139]. Although studies on cadavers led to greatly improved knowledge of the anatomy of the human vascular system, angiography in living man for the purpose of diagnosis and intervention became feasible only after substantial progress in the development yA term originating from the Greek words o (aggeion), meaning \vessel" or \bucket", and -' (graphein), meaning \to write" or \to record". 2 1 Introduction and Summary of relatively safe contrast media and methods of administration, as well as advance- ments in radiological equipment. Of special interest in the context of this thesis is the improvement brought by photographic subtraction, a technique known since the early 1900s and since then used successfully in e.g. astronomy, but rst introduced in X-ray angiography in 1934, by Ziedses des Plantes [425, 426]. This technique al- lowed for a considerable enhancement of vessel visibility by cancellation of unwanted background structures. In the 1960s, the time consuming lm subtraction process was replaced by analog video subtraction techniques [156, 275] which, with the in- troduction of digital computers, gave rise to the development of digital subtraction angiography [194] | a technique still considered by many the \gold standard" for de- tection and quantication of vascular anomalies. Today, research on improved X-ray based imaging techniques for angiography continues, witness the recent developments in three-dimensional rotational angiography [88, 185, 186, 341,373]. The subject of this thesis is enhancement of digital X-ray angiography images. In contrast with the previously mentioned developments, the emphasis is not on the further improvement of image acquisition techniques, but rather on the development and evaluation of digital image processing techniques for retrospective enhancement of images acquired with existing techniques. In the context of this thesis, the term \enhancement" must be regarded in a rather broad sense. It does not only refer to improvement of image quality by reduction of disturbing artifacts and noise, but also to minimization of possible image quality degradation and loss of quantitative information, inevitably introduced by required image processing operations. These two aspects of image enhancement will be claried further in a brief summary of each of the chapters of this thesis. The rst three chapters deal with the problem of patient motion artifacts in digital subtraction angiography (DSA). In DSA imaging, a sequence of 2D digital X-ray projection images is acquired, at a rate of e.g. two per second, following the injection of contrast material into one of the arteries or veins feeding the part of the vasculature to be diagnosed. Acquisition usually starts about one or two seconds prior to arrival of the contrast bolus in the vessels of interest, so that the rst few images included in the sequence do not show opacied vessels. In a subsequent post-processing step, one of these \pre-bolus" images is then subtracted automatically from each of the contrast images so as to mask out background structures such as bone and soft- tissue shadows. However, it is clear that in the resulting digital subtraction images, the unwanted background structures will have been removed completely only when the patient lied perfectly still during acquisition of the original images. Since most patients show at least some physical reaction to the passage of a contrast medium, this proviso is generally not met. As a result, DSA images frequently show patient-motion induced artifacts (see e.g. the bottom-left image in Fig. 1.1), which may in uence the subsequent analysis and diagnosis carried out by radiologists. Since the introduction of DSA, in the early 1980s, many solutions to the problem of patient motion artifacts have been put forward. Chapter 2 presents an overview of the possible types of motion artifacts reported in the literature and the techniques that have been proposed to avoid them. The main purpose of that chapter is to review and discuss the techniques proposed over the past two decades to correct for 1 Introduction and Summary 3 Figure 1.1. Example of creation and reduction of patient motion artifacts in cerebral DSA imaging. Top left: a \pre-bolus" or mask image acquired just prior to the arrival of the contrast medium. Top right: one of the contrast or live images showing opacied vessels. Bottom left: DSA image obtained after subtraction of the mask from the contrast image, followed by contrast enhancement. Due to patient motion, the background structures in the mask and contrast image were not perfectly aligned, as a result of which the DSA image does not only show blood vessels, but also additional undesired structures (in this example primarily in the bottom-left part of the image). Bottom right: DSA image resulting from subtraction of the mask and contast image after application of the automatic registration algorithm described in Chapter 3. 4 1 Introduction and Summary patient motion artifacts retrospectively, by means of digital image processing. The chapter addresses fundamental problems, such as whether it is possible to construct a 2D geometrical transformation that exactly describes the projective eects of an originally 3D transformation, as well as practical problems, such as how to retrieve the correspondence between mask and contrast images by using only the grey-level information contained in the images, and how to align the images according to that correspondence in a computationally ecient manner. The review in Chapter 2 reveals that there exists quite some literature on the topic of (semi-)automatic image alignment, or image registration, for the purpose of motion artifact reduction in DSA images. However, to the best of our knowledge, research in this area has never led to algorithms which are suciently fast and robust to be acceptable for routine use in clinical practice. By drawing upon the suggestions put forward in Chapter 2, a new approach to automatic registration of digital X-ray angiography images is presented in Chapter 3. Apart from describing the functionality of the components of the algorithm, special attention is paid to their computationally optimal implementation. The results of preliminary experiments described in that chapter indicate that the algorithm is eective, very fast, and outperforms alterna- tive approaches, in terms of both image quality and required computation time. It is concluded that the algorithm is most eective in cerebral and peripheral DSA imag- ing. An example of the image quality enhancement obtained after application of the algorithm in the case of a cerebral DSA image is provided in Fig 1.1. Chapter 4 reports on a clinical evaluation of the automatic registration technique. The evaluation involved 104 cerebral DSA images, which were corrected for patient motion artifacts by the automatic technique, as well as by pixel shifting | a manual correction technique currently used in clinical practice. The quality of the DSA images resulting from the two techniques was assessed by four observers, who compared the images both mutually and to the corresponding original images. The results of the evaluation presented in Chapter 4 indicate that the dierence in performance between the two correction techniques is statistically signicant. From the results of the mutual comparisons it is concluded that, on average, the automatic registration technique performs either comparably, better than, or even much better than manual pixel shifting in 95% of all cases. In the other 5% of the cases, the remaining artifacts are located near the borders of the image, which are generally diagnostically non-relevant. In addition, the results show that the automatic technique implies a considerable reduction of post-processing time compared to manual pixel shifting (on average, one second versus 12 seconds per DSA image). The last two chapters deal with somewhat dierent topics. Chapter 5 is concerned with visualization and quantication of vascular anomalies in three-dimensional rota- tional angiography (3DRA). Similar to DSA imaging, 3DRA involves the acquisition of a sequence of 2D digital X-ray projection images, following a single injection of contrast material. Contrary to DSA, however, this sequence is acquired during a 180 rotation of the C-arch on which the X-ray source and detector are mounted antipo- dally, with the object of interest positioned in its iso-center. The rotation is completed in about eight seconds and the resulting image sequence typically contains 100 images, which form the input to a ltered back-projection algorithm for 3D reconstruction. In contrast with most other 3D medical imaging techniques, 3DRA is capable of provid- 1 Introduction and Summary 5 Figure 1.2. Visualizations of a clinical 3DRA dataset, illustrating the qualitative improvement obtained after noise reduction ltering. Left: volume rendering of the original, raw image. Right: volume rendering of the image after application of edge-enhancing anisotropic diusion ltering (see Chapter 5 for a description of this technique). The visualizations were obtained by using the exact same settings for the parameters of the volume rendering algorithm. ing high-resolution isotropic datasets. However, due to the relatively high noise level and the presence of other unwanted background variations caused by surrounding tissue, the use of noise reduction techniques is inevitable in order to obtain smooth visualizations of these datasets (see Fig. 1.2). Chapter 5 presents an inquiry into the eects of several linear and nonlinear noise reduction techniques on the visualization and subsequent quantication of vascular anomalies in 3DRA images. The evalua- tion is focussed on frequently occurring anomalies such as a narrowing (or stenosis) of the internal carotid artery or a circumscribed dilation (or aneurysm) of intracra- nial arteries. Experiments on anthropomorphic vascular phantoms indicate that, of the techniques considered, edge-enhancing anisotropic diusion ltering is most suit- able, although the practical use of this technique may currently be limited due to its memory and computation-time requirements. Finally, Chapter 6 addresses the problem of interpolation of sampled data, which occurs e.g. when applying geometrical transformations to digital medical images for the purpose of registration or visualization. In most practical situations, interpola- tion of a sampled image followed by resampling of the resulting continuous image on a geometrically transformed grid, inevitably implies loss of grey-level information, and hence image degradation, the amount of which is dependent on image content, but also on the employed interpolation scheme (see Fig. 1.3). It follows that the choice for a particular interpolation scheme is important, since it in uences the re- sults of registrations and visualizations, and the outcome of subsequent quantitative analyses which rely on grey-level information contained in transformed images. Al- though many interpolation techniques have been developed over the past decades, 6 1 Introduction and Summary Figure 1.3. Illustration of the fact that the loss of information due to interpola- tion and resampling operations is dependent on the employed interpolation scheme. Left: slice of a 3DRA image after rotation over 5:0, by using linear interpolation. Middle: the same slice, after rotation by using cubic spline interpolation. Right: the dierence between the two rotated images. Although it is not possible with such a comparison to come to conclusions as to which of the two methods yields the smallest loss of grey-level information, this example clearly illustrates the point that dierent interpolation methods usually yield dierent results. thorough quantitative evaluations and comparisons of these techniques for medical image transformation problems are still lacking. Chapter 6 presents such a compar- ative evaluation. The study is limited to convolution-based interpolation techniques, as these are most frequently used for registration and visualization of medical image data. Because of the ubiquitousness of interpolation in medical image processing and analysis, the study is not restricted to XRA and 3DRA images, but also includes datasets from many other modalities. It is concluded that for all modalities, spline interpolation constitutes the best trade-o between accuracy and computational cost, and therefore is to be preferred over all other methods. In summary, this thesis is concerned with the improvement of image quality and the reduction of image quality degradation and loss of quantitative information. The subsequent chapters describe techniques for reduction of patient motion artifacts in DSA images, noise reduction techniques for improved visualization and quantication of vascular anomalies in 3DRA images, and interpolation techniques for the purpose of accurate geometrical transformation of medical image data. The results and con- clusions of the evaluations described in this thesis provide general guidelines for the applicability and practical use of these techniques

Artifacts due to dental and maxillofacial restoration materials in cone beam computed tomography images

Over the last 20 years, three-dimensional X-ray imaging, cone beam computed tomography (CBCT), has become an important method when making the diagnoses in the dental and maxillofacial area. There has been rapid development in CBCT devices, and the image quality has improved considerably during the last two decades. Despite the many improvements in CBCT image quality, artifacts induced by dental and maxillofacial restoration materials are still a problem, especially when diagnosing the dental area. CBCT manufacturers produce artifact reduction algorithms, which are intended to decrease or remove the artifacts in the image. However, the results of the studies on artifact reduction algorithms vary and there is no final consensus, as yet, on their efficacy. The studies of the present thesis focus on the arti-facts induced by different dental restoration materials in CBCT images. Another aim was to compare how the different materials interfere with the radiologic diagnosis. The materials investigated were titanium, zirconia, composite, and fiber reinforced composite (FRC). The results showed that composites with ra-dio-opacifying BaAlSiO2 20% (weight%) or more caused artifacts in the CBCT images. Composites with BaAlSiO2 68% (weight%) or more caused artifacts with similar intensity as titanium. Titanium orbital floor implant caused artifacts in the CBCT images, whereas nonmetallic fiber reinforced composite (FRC) orbital floor implant did not cause hampering artifacts in the CBCT images. The diagnosis of apical perio-dontitis can be complicated in 70% of the CBCT images of paranasal sinuses because of the artifacts induced by dental and endodontic restorations. In the CBCT images, zirconia dental implants caused in-tense artifacts despite the artifact reduction algorithm. To conclude, different dental restoration materials cause image hampering artifacts of different intensities in CBCT images. Zirconia is especially problem-atic in CBCT images. More studies are needed on artifact reduction methods to achieve an image quality without artifacts to make the correct diagnosis. In addition, the consequences of restoration and implant material options should be considered in postoperative CBCT images

Medical Image Enhancement using Deep Learning and Tensor Factorization Techniques

La résolution spatiale des images acquises par tomographie volumique à faisceau conique (CBCT) est limitée par la géométrie des capteurs, leur sensibilité, les mouvements du patient, les techniques de reconstruction d'images et la limitation de la dose de rayonnement. Le modèle de dégradation d'image considéré dans cette thèse consiste en un opérateur de ou avec la fonction d'étalement du système d'imagerie (PSF), un opérateur de décimation, et du bruit, qui relient les volumes CBCT à une image 3D super-résolue à estimer. Les méthodes proposées dans cette thèse (SISR - single image super-résolution) ont comme objectif d'inverser ce modèle direct, c'est à dire d'estimer un volume haute résolution à partir d'une image CBCT. Les algorithmes ont été évalués dans le cadre d'une application dentaire, avec comme vérité terrain les images haute résolution acquises par micro CT (µCT), qui utilise des doses de rayonnement très importantes, incompatibles avec les applications cliniques. Nous avons proposé une approche de SISR par deep learning, appliquée individuellement à des coupes CBCT. Deux types de réseaux ont été évalués : U-net et subpixel. Les deux ont amélioré les volumes CBCT, avec un gain en PSNR de 21 à 22 dB et en coefficient de Dice pour la segmentation canalaire de 1 à 2.2 %. Le gain a été plus particulièrement important dans la partie apicale des dents, ce qui représente un résultat important étant donnée son importance pour les applications cliniques. Nous avons proposé des algorithmes de SISR basés sur la décomposition canonique polyadique des tenseurs. Le principal avantage de cette méthode, lié à l'utilisation de la théorie des tenseur, est d'utiliser la structure 3D des volumes CBCT. L'algorithme proposé regroupe plusieurs étapes: débruitage base sur la factorisation des tenseurs, déconvolution et super-résolution, avec un faible nombre d'hyperparamètres. Le temps d'exécution est très faible par rapport aux algorithmes existants (deux ordres de magnitude plus petit), pour des performances légèrement supérieures (gain de 1.2 à 1.5 dB en PSNR). La troisième contribution de la thèse est en lien avec la contribution 2 : l'algorithme de SISR basé sur la décomposition canonique polyadique des tenseurs est combiné avec une méthode d'estimation de la PSF, inconnues dans les applications pratiques. L'algorithme résultant effectue les deux tâche de manière alternée, et s'avère précis et rapide sur des données de simulation et expérimentales. La dernière contribution de la thèse a été d'évaluer l'intérêt d'un autre type de décomposition tensorielle, la décomposition de Tucker, dans le cadre d'un algorithme de SISR. Avant la déconvolution, le volume CBCT est débruité en tronquant sa décomposition de Tucker. Comparé à l'algorithme de la contribution 2, cette approche permet de diminuer encore plus le temps de calcul, d'un facteur 10, pour des performances similaires pour des SNR importants et légèrement supérieures pour de faibles SNR. Le lien entre cette méthode et les algorithmes 2D basés sur une SVD facilite le réglage des hyperparamètres comparé à la décomposition canonique polyadique.The resolution of dental cone beam computed tomography (CBCT) images is imited by detector geometry, sensitivity, patient movement, the reconstruction technique and the need to minimize radiation dose. The corresponding image degradation model assumes that the CBCT image is a blurred (with a point spread function, PSF), downsampled, noisy version of a high resolution image. The quality of the image is crucial for precise diagnosis and treatment planning. The methods proposed in this thesis aim to give a solution for the single image super-resolution (SISR) problem. The algorithms were evaluated on dental CBCT and corresponding highresolution (and high radiation-dose) µCT image pairs of extracted teeth. I have designed a deep learning framework for the SISR problem, applied to CBCT slices. I have tested the U-net and subpixel neural networks, which both improved the PSNR by 21-22 dB, and the Dice coe_cient of the canal segmentation by 1-2.2%, more significantly in the medically critical apical region. I have designed an algorithm for the 3D SISR problem, using the canonical polyadic decomposition of tensors. This implementation conserves the 3D structure of the volume, integrating the factorization-based denoising, deblurring with a known PSF, and upsampling of the image in a lightweight algorithm with a low number of parameters. It outperforms the state-of-the-art 3D reconstruction-based algorithms with two orders of magnitude faster run-time and provides similar PSNR (improvement of 1.2-1.5 dB) and segmentation metrics (Dice coe_cient increased on average to 0.89 and 0.90). Thesis II b: I have implemented a joint alternating recovery of the unknown PSF parameters and of the high-resolution 3D image using CPD-SISR. The algorithm was compared to a state-of-the-art 3D reconstruction-based algorithm, combined with the proposed alternating PSF-optimization. The two algorithms have shown similar improvement in PSNR, but CPD-SISR-blind converged roughly 40 times faster, under 6 minutes both in simulation and on experimental dental computed tomography data. I have proposed a solution for the 3D SISR problem using the Tucker decomposition (TD-SISR). The denoising step is realized _rst by TD in order to mitigate the ill-posedness of the subsequent deconvolution. Compared to CPDSISR the algorithm runs ten times faster. Depending on the amount of noise, higher PSNR (0.3 - 3.5 dB), SSI (0.58 - 2.43%) and segmentation values (Dice coefficient, 2% improvement) were measured. The parameters in TD-SISR are familiar from 2D SVD-based algorithms, so their tuning is easier compared to CPD-SISR

Efficient sampling strategies for x-ray micro computed tomography with an intensity-modulated beam

The term "cycloidal CT" refers to a family of efficient sampling strategies that can be applied to x-ray micro-computed tomography (CT) systems which operate with an intensity-modulated beam. Such a beam can be employed to provide access to a phase contrast channel and high spatial resolutions (a few um). Phase contrast can offer better image contrast of samples which have traditionally been "invisible” to x-rays due to their weak attenuation, and high resolutions help view crucial details in samples. Cycloidal sampling strategies provide images more quickly than the gold standard in the field ("dithering”). I conceived and compared four practical implementation strategies for cycloidal CT, three of which are "flyscans” (the sample moves continuously). Flyscans acquire images of similar resolution to dithering with no overheads, reducing acquisition time to exposure time. I also developed a "knife-edge” position tracking method which tracks subpixel motions of the sample stage. This information can be used to facilitate, automate, and improve the reconstruction of cycloidal data. I analysed the effects of different levels of dose on the signal-to-noise ratio (SNR) of an image acquired with cycloidal CT. The results show that cycloidal images yield the same SNR as dithered images with less dose, although a more extensive study is required. Finally, I explored the potential of using cycloidal CT for intraoperative specimen imaging and tissue engineering. My results are encouraging for tissue engineering; for intraoperative imaging, the cycloidal images did not show comparable resolution to the dithered images, although that is possibly linked to issues with the dataset. Overall, my work has provided a benchmark for the implementation and application of cycloidal CT for the first time. Besides a summary of my research, this thesis is meant to be a comprehensive guide for facilitating uptake of cycloidal CT within the scientific community and beyond

Development and application of an optogenetic platform for controlling and imaging a large number of individual neurons

The understanding and treatment of brain disorders as well as the development of intelligent machines is hampered by the lack of knowledge of how the brain fundamentally functions. Over the past century, we have learned much about how individual neurons and neural networks behave, however new tools are critically needed to interrogate how neural networks give rise to complex brain processes and disease conditions. Recent innovations in molecular techniques, such as optogenetics, have enabled neuroscientists unprecedented precision to excite, inhibit and record defined neurons. The impressive sensitivity of currently available optogenetic sensors and actuators has now enabled the possibility of analyzing a large number of individual neurons in the brains of behaving animals. To promote the use of these optogenetic tools, this thesis integrates cutting edge optogenetic molecular sensors which is ultrasensitive for imaging neuronal activity with custom wide field optical microscope to analyze a large number of individual neurons in living brains. Wide-field microscopy provides a large field of view and better spatial resolution approaching the Abbe diffraction limit of fluorescent microscope. To demonstrate the advantages of this optical platform, we imaged a deep brain structure, the Hippocampus, and tracked hundreds of neurons over time while mouse was performing a memory task to investigate how those individual neurons related to behavior. In addition, we tested our optical platform in investigating transient neural network changes upon mechanical perturbation related to blast injuries. In this experiment, all blasted mice show a consistent change in neural network. A small portion of neurons showed a sustained calcium increase for an extended period of time, whereas the majority lost their activities. Finally, using optogenetic silencer to control selective motor cortex neurons, we examined their contributions to the network pathology of basal ganglia related to Parkinson’s disease. We found that inhibition of motor cortex does not alter exaggerated beta oscillations in the striatum that are associated with parkinsonianism. Together, these results demonstrate the potential of developing integrated optogenetic system to advance our understanding of the principles underlying neural network computation, which would have broad applications from advancing artificial intelligence to disease diagnosis and treatment

Accurate 3D-reconstruction and -navigation for high-precision minimal-invasive interventions

The current lateral skull base surgery is largely invasive since it requires wide exposure and direct visualization of anatomical landmarks to avoid damaging critical structures. A multi-port approach aiming to reduce such invasiveness has been recently investigated. Thereby three canals are drilled from the skull surface to the surgical region of interest: the first canal for the instrument, the second for the endoscope, and the third for material removal or an additional instrument. The transition to minimal invasive approaches in the lateral skull base surgery requires sub-millimeter accuracy and high outcome predictability, which results in high requirements for the image acquisition as well as for the navigation. Computed tomography (CT) is a non-invasive imaging technique allowing the visualization of the internal patient organs. Planning optimal drill channels based on patient-specific models requires high-accurate three-dimensional (3D) CT images. This thesis focuses on the reconstruction of high quality CT volumes. Therefore, two conventional imaging systems are investigated: spiral CT scanners and C-arm cone-beam CT (CBCT) systems. Spiral CT scanners acquire volumes with typically anisotropic resolution, i.e. the voxel spacing in the slice-selection-direction is larger than the in-the-plane spacing. A new super-resolution reconstruction approach is proposed to recover images with high isotropic resolution from two orthogonal low-resolution CT volumes. C-arm CBCT systems offers CT-like 3D imaging capabilities while being appropriate for interventional suites. A main drawback of these systems is the commonly encountered CT artifacts due to several limitations in the imaging system, such as the mechanical inaccuracies. This thesis contributes new methods to enhance the CBCT reconstruction quality by addressing two main reconstruction artifacts: the misalignment artifacts caused by mechanical inaccuracies, and the metal-artifacts caused by the presence of metal objects in the scanned region. CBCT scanners are appropriate for intra-operative image-guided navigation. For instance, they can be used to control the drill process based on intra-operatively acquired 2D fluoroscopic images. For a successful navigation, accurate estimate of C-arm pose relative to the patient anatomy and the associated surgical plan is required. A new algorithm has been developed to fulfill this task with high-precision. The performance of the introduced methods is demonstrated on simulated and real data

Image Registration Workshop Proceedings

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research

Robust density modelling using the student's t-distribution for human action recognition

The extraction of human features from videos is often inaccurate and prone to outliers. Such outliers can severely affect density modelling when the Gaussian distribution is used as the model since it is highly sensitive to outliers. The Gaussian distribution is also often used as base component of graphical models for recognising human actions in the videos (hidden Markov model and others) and the presence of outliers can significantly affect the recognition accuracy. In contrast, the Student's t-distribution is more robust to outliers and can be exploited to improve the recognition rate in the presence of abnormal data. In this paper, we present an HMM which uses mixtures of t-distributions as observation probabilities and show how experiments over two well-known datasets (Weizmann, MuHAVi) reported a remarkable improvement in classification accuracy. © 2011 IEEE