Point-Spread-Function-Aware Slice-to-Volume Registration: Application to Upper Abdominal MRI Super-Resolution

MR image acquisition of moving organs remains challenging despite the advances in ultra-fast 2D MRI sequences. Post-acquisition techniques have been proposed to increase spatial resolution a posteriori by combining acquired orthogonal stacks into a single, high-resolution (HR) volume. Current super-resolution techniques classically rely on a two-step procedure. The volumetric reconstruction step leverages a physical slice acquisition model. However, the motion correction step typically neglects the point spread function (PSF) information. In this paper, we propose a PSF-aware slice-to-volume registration approach and, for the first time, demonstrate the potential benefit of Super-Resolution for upper abdominal imaging. Our novel reconstruction pipeline takes advantage of different MR acquisitions clinically used in routine MR cholangiopancreatography studies to guide the registration. On evaluation of clinically relevant image information, our approach outperforms state-of-the-art reconstruction toolkits in terms of visual clarity and preservation of raw data information. Overall, we achieve promising results towards replacing currently required CT scans

Szinkronizált beszéd- és nyelvultrahang-felvételek a SonoSpeech rendszerrel

Kivonat: A jelen ismertetés az MTA–ELTE Lingvális Artikuláció Kutatócsoport ultrahangos vizsgálatainak technikai hátterét, az alkalmazott hardver- és szoftverkörnyezetet, illetőleg a folyó és tervezett kutatásokat mutatja be. A magyar és nemzetközi szakirodalmi előzmények tárgyalása után ismerteti az ultrahangnak mint az artikuláció vizsgálatában alkalmazott eszköznek a sajátosságait, összevetve más kísérleti eszközökkel és módszertanokkal. Kitér a kutatási nehézségekre is, mint például az ultrahangkép beszélőfüggő minősége, a nyelvkontúr manuális és automatikus meghatározása, végül bemutatja a kutatócsoport főbb céljait és terveit, mind az alap-, mind pedig az alkalmazott kutatások területén

Integrated Segmentation and Interpolation of Sparse Data

This paper addresses the two inherently related problems of segmentation and interpolation of 3D and 4D sparse data by integrating integrate these stages in a level set framework. The method supports any spatial configurations of sets of 2D slices having arbitrary positions and orientations. We introduce a new level set scheme based on the interpolation of the level set function by radial basis functions. The proposed method is validated quantitatively and/or subjectively on artificial data and MRI and CT scans and is compared against the traditional sequential approach

Integrated Segmentation and Interpolation of Sparse Data

International audienceWe address the two inherently related problems of segmentation and interpolation of 3D and 4D sparse data and propose a new method to integrate these stages in a level set framework. The interpolation process uses segmentation information rather than pixel intensities for increased robustness and accuracy. The method supports any spatial configurations of sets of 2D slices having arbitrary positions and orientations. We achieve this by introducing a new level set scheme based on the interpolation of the level set function by radial basis functions. The proposed method is validated quantitatively and/or subjectively on artificial data and MRI and CT scans, and is compared against the traditional sequential approach which interpolates the images first, using a state-of-the-art image interpolation method, and then segments the interpolated volume in 3D or 4D. In our experiments, the proposed framework yielded similar segmentation results to the sequential approach, but provided a more robust and accurate interpolation. In particular, the interpolation was more satisfactory in cases of large gaps, due to the method taking into account the global shape of the object, and it recovered better topologies at the extremities of the shapes where the objects disappear from the image slices. As a result, the complete integrated framework provided more satisfactory shape reconstructions than the sequential approach

Super-resolution for upper abdominal MRI: Acquisition and post-processing protocol optimization using brain MRI control data and expert reader validation

Purpose Magnetic resonance (MR) cholangiopancreatography (MRCP) is an established specialist method for imaging the upper abdomen and biliary/pancreatic ducts. Due to limitations of either MR image contrast or low through‐plane resolution, patients may require further evaluation with contrast‐enhanced computed tomography (CT) images. However, CT fails to offer the high tissue‐ductal‐vessel contrast‐to‐noise ratio available on T2‐weighted MR imaging. Methods MR super‐resolution reconstruction (SRR) frameworks have the potential to provide high‐resolution visualizations from multiple low through‐plane resolution single‐shot T2‐weighted (SST2W) images as currently used during MRCP studies. Here, we (i) optimize the source image acquisition protocols by establishing the ideal number and orientation of SST2W series for MRCP SRR generation, (ii) optimize post‐processing protocols for two motion correction candidate frameworks for MRCP SRR, and (iii) perform an extensive validation of the overall potential of upper abdominal SRR, using four expert readers with subspeciality interest in hepato‐pancreatico‐biliary imaging. Results Obtained SRRs show demonstrable advantages over traditional SST2W MRCP data in terms of anatomical clarity and subjective radiologists’ preference scores for a range of anatomical regions that are especially critical for the management of cancer patients. Conclusions Our results underline the potential of using SRR alongside traditional MRCP data for improved clinical diagnosis

Desenvolvimento da língua e sua relação com deglutição e sucção pré-natais

TCC(graduação) - Universidade Federal de Santa Catarina. Centro de Ciências da Saúde. Fonoaudiologia.Introdução: A língua é uma estrutura muscular, tendo o início de seu desenvolvimento no final da 4ª semana do desenvolvimento embrionário. Dentre as estruturas envolvidas na sucção e deglutição, a língua tem um papel fundamental, sendo essas funções iniciadas na vida intrauterina. Metodologia: O presente trabalho consiste de uma revisão da literatura descritiva sobre o desenvolvimento da língua e a sua relação com os mecanismos da deglutição e sucção no período pré-natal, por meio de um levantamento bibliográfico em livros da área e artigos científicos relacionados ao tema. Revisão de Literatura: A crista neural é uma população de células embrionárias que são multipotentes e com propriedades migratórias, presente apenas em embriões de vertebrados. Em embriões humanos, o desenvolvimento da cabeça e do pescoço envolve a formação do aparelho faríngeo, que contém diferentes células embrionárias: ectoderma, endoderma, mesoderma e as células da crista neural. A língua surge no final da 4a semana a partir da formação de 5 saliências mesenquimais, originadas do 1o a 4o par de arcos faríngeos: a saliência lingual mediana, as duas saliências linguais laterais, a cópula e a saliência hipofaríngea. A língua é um órgão que desempenha funções fisiológicas essenciais. A deglutição e a sucção são movimentos que possuem um papel importante durante a vida intrauterina e para a sobrevivência do recém-nascido. Discussão: Os primeiros sinais do início da morfogênese da língua são pouco compreendidos. Em contrapartida, informações referentes a língua adulta são bastante estudadas e encontram-se bem descritas em publicações especializadas. Estudos mostram que o mecanismo da deglutição na vida intrauterina contribui de maneira importante para vários processos críticos do desenvolvimento. Poucos estudos foram realizados revelando a atividade de sucção durante o período pré-natal. Considerações Finais: O bom funcionamento dessas funções desde o período pré-natal reflete em toda a vida do indivíduo, sendo a formação adequada das estruturas o fator que possibilita a execução ideal das funções estomatognáticas.Introduction: The tongue is a muscular structure. Its development begins at the end of the 4th week of the embryonic development. Among the structures involved in sucking and swallowing, the tongue has a key role, being that functions initiate in intrauterine life. Methodology: This study is a descriptive literature review on the development of tongue and its relation to the mechanisms of swallowing and sucking in the prenatal period, through a literature survey in books and scientific articles related to this topic. Literature Review: The neural crest is a population of stem cells that are multipotent and hold migratory properties, present only in vertebrate embryos. In human embryos, the development of head and neck involves the formation of pharyngeal apparatus containing different embryonic cells: ectoderm, endoderm, mesoderm and neural crest cells. The tongue appears at the end of the fourth week from the formation of 5 mesenchymal protrusions originating from the first to fourth pair of pharyngeal archs: tongue protrusion median, two lateral tongue protrusions, copulation and hypopharynx protrusion. The tongue is a organ that plays essential physiological functions. The sucking and swallowing movements have an important role during intrauterine life and in the survival of the newborn. Discussion: The first signs of the onset of the tongue morphogenesis are poorly understood. In contrast, information regarding adult tongue are vast and are well described in current literature. Studies show that the mechanism of swallowing during intrauterine life contributes significantly to several critical developmental processes. Few studies have been conducted revealing the sucking activity during the prenatal period. Conclusion: The proper functioning from the prenatal period reflects throughout the life of the newborn, and the proper formation of the oral structures are key factors that allow the optimal performance of stomatognathic functions

Filter Design and Consistency Evaluation for 3D Tongue Motion Estimation using Harmonic Phase Analysis Method

Understanding patterns of tongue motion in speech using 3D motion estimation is challenging. Harmonic phase analysis has been used to perform noninvasive tongue motion and strain estimation using tagged magnetic resonance imaging (MRI). Two main contributions have been made in this thesis. First, the filtering process, which is used to produce harmonic phase images used for tissue tracking, influences the estimation accuracy. For this work, we evaluated different filtering approaches, and propose a novel high-pass filter for volumes tagged in individual directions. Testing was done using an open benchmarking dataset and synthetic images obtained using a mechanical model. Second, the datasets with inconsistent motion need to be excluded to yield meaningful motion estimation. For this work, we used a tracking-based method to evaluate the motion consistency between datasets and gave a strategy to identify the inconsistent dataset. Experiments including 2 normal subjects were done to validate our method. In all, the first work about 3D filter design improves the motion estimation accuracy and the second work about motion consistency test ensures the meaningfulness of the estimation results

Facial soft tissue segmentation

The importance of the face for socio-ecological interaction is the cause for a high demand on any surgical intervention on the facial musculo-skeletal system. Bones and soft-tissues are of major importance for any facial surgical treatment to guarantee an optimal, functional and aesthetical result. For this reason, surgeons want to pre-operatively plan, simulate and predict the outcome of the surgery allowing for shorter operation times and improved quality. Accurate simulation requires exact segmentation knowledge of the facial tissues. Thus semi-automatic segmentation techniques are required. This thesis proposes semi-automatic methods for segmentation of the facial soft-tissues, such as muscles, skin and fat, from CT and MRI datasets, using a Markov Random Fields (MRF) framework. Due to image noise, artifacts, weak edges and multiple objects of similar appearance in close proximity, it is difficult to segment the object of interest by using image information alone. Segmentations would leak at weak edges into neighboring structures that have a similar intensity profile. To overcome this problem, additional shape knowledge is incorporated in the energy function which can then be minimized using Graph-Cuts (GC). Incremental approaches by incorporating additional prior shape knowledge are presented. The proposed approaches are not object specific and can be applied to segment any class of objects be that anatomical or non-anatomical from medical or non-medical image datasets, whenever a statistical model is present. In the first approach a 3D mean shape template is used as shape prior, which is integrated into the MRF based energy function. Here, the shape knowledge is encoded into the data and the smoothness terms of the energy function that constrains the segmented parts to a reasonable shape. In the second approach, to improve handling of shape variations naturally found in the population, the fixed shape template is replaced by a more robust 3D statistical shape model based on Probabilistic Principal Component Analysis (PPCA). The advantages of using the Probabilistic PCA are that it allows reconstructing the optimal shape and computing the remaining variance of the statistical model from partial information. By using an iterative method, the statistical shape model is then refined using image based cues to get a better fitting of the statistical model to the patient's muscle anatomy. These image cues are based on the segmented muscle, edge information and intensity likelihood of the muscle. Here, a linear shape update mechanism is used to fit the statistical model to the image based cues. In the third approach, the shape refinement step is further improved by using a non-linear shape update mechanism where vertices of the 3D mesh of the statistical model incur the non-linear penalty depending on the remaining variability of the vertex. The non-linear shape update mechanism provides a more accurate shape update and helps in a finer shape fitting of the statistical model to the image based cues in areas where the shape variability is high. Finally, a unified approach is presented to segment the relevant facial muscles and the remaining facial soft-tissues (skin and fat). One soft-tissue layer is removed at a time such as the head and non-head regions followed by the skin. In the next step, bones are removed from the dataset, followed by the separation of the brain and non-brain regions as well as the removal of air cavities. Afterwards, facial fat is segmented using the standard Graph-Cuts approach. After separating the important anatomical structures, finally, a 3D fixed shape template mesh of the facial muscles is used to segment the relevant facial muscles. The proposed methods are tested on the challenging example of segmenting the masseter muscle. The datasets were noisy with almost all possessing mild to severe imaging artifacts such as high-density artifacts caused by e.g. dental fillings and dental implants. Qualitative and quantitative experimental results show that by incorporating prior shape knowledge leaking can be effectively constrained to obtain better segmentation results