Lung is the most important gas exchange organ of human, and the smooth airway is the basis of lung function. The condition of the trachea is associated with a variety of diseases. In this paper ...several methods of tracheal simulation based on CT-based data since 2003 are reviewed. Reasonable algorithms and image processing methods are important development directions for airway scanning reconstruction. The development of airway reconstruction needs to be closely integrated with mathematical modelling to improve the accuracy and precision of reconstruction.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
To present a case of a 56 y.o. male with maxillo-facial trauma after falling from heights and the possibility to choice the treatment tactics based on CT volume calculation. Material and methods. ...Patient N., 56 years old, came to the clinic 3 days after the injury – a fall from heights. During the examination in the clinic, the patient did not have visual impairments and difficulties in eye movement. We performed MSCT of the maxillofacial region, which revealed radiological signs of fractures of the lower and lateral walls of the right orbit. In order to determine further treatment tactics for this patient (surgical treatment or conservative therapy), the authors performed additional processing of MSCT data in order to obtain clarifying diagnostic information. Results. The authors performed the calculation of orbital volumes and confirmed the possible minimal risk of post-traumatic complications such as enophthalmos and hypophthalmos. It was decided to treat the patient conservatively. The long-term follow-up MSCT study confirmed the correct management of a patient with orbital trauma in terms of restoration of the right orbit walls with minimal volumetric change. Conclusion. This case highlights the advantage of using new techniques of CT data processing in daily practice.
Pressure sensitivity research on the head, face, and neck is critical to develop ways to reduce discomfort caused by pressure in head-related products. The aim of this paper is to provide information ...for designers to be able to reduce the pressure discomfort by studying the relation between pressure sensitivity and soft tissue in the head, face and neck. We collected pressure discomfort threshold (PDT) and pressure pain threshold (PPT) from 119 landmarks (unilateral) for 36 Chinese subjects. Moreover, soft tissue thickness data on the head, face and neck regions of 50 Chinese people was obtained through CT scanning while tissue deformation data under the PDT and PPT states was obtained from literature. The results of the three-elements correlation analysis revealed that soft tissue thickness is positively correlated with deformation but not an important factor in pressure sensitivity. Our high-precision pressure sensitivity maps confirm earlier findings of more rough pressure sensitivity studies, while also revealing additional fine scale sensitivity differences. Finally, based on the findings, a high-precision "recommended map” of the optimal stress-bearing area of the head, face and neck was generated.
•Soft tissue thickness is not an important factor affecting pressure sensitivity.•The thicker the soft tissue, the greater the degree of soft tissue deformation.•The results show that the pressure thresholds for the scalp are the highest, followed by the neck and face.•Our pressure sensitivity maps revealing additional fine scale sensitivity differences compared with previous study.•High-precision pressure sensitivity maps, soft tissue thickness maps and an optimal stress-bearing area map were generated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Purpose
In the clinic, computed tomography (CT) has evolved into an essential modality for diagnostic imaging by multidetector row CT (MDCT) and image guided intervention by cone beam CT (CBCT). ...Recognizing the increasing importance of axial MDCT/CBCT in clinical and preclinical applications, and the existence of CB artifacts in MDCT/CBCT images, we provide a review of CB artifacts’ root causes, rendering mechanisms and morphology, and possible solutions for elimination and/or reduction of the artifacts.
Methods
By examining the null space in Radon and Fourier domain, the root cause of CB artifacts (i.e., data insufficiency) in axial MDCT/CBCT is analytically investigated, followed by a review of the data sufficiency conditions and the “circle +” source trajectories. The rendering mechanisms and morphology of CB artifacts in axial MDCT/CBCT and their special cases (e.g., half/short scan and full scan with latitudinally displaced detector) are then analyzed, followed by a survey of the potential solutions to suppress the artifacts. The phenomenon of imaged zone indention and its variation over FBP, BPF/DBPF, two‐pass and iterative CB reconstruction algorithms and/or schemes are discussed in detail.
Results
An interdomain examination of the null space provides an insightful understanding of the root cause of CB artifacts in axial MDCT/CBCT. The decomposition of CB artifacts rendering mechanisms facilitates understanding of the artifacts’ behavior under different conditions and the potential solutions to suppress them. An inspection of the imaged zone intention phenomenon provides guidance on the design and implementation of CB image reconstruction algorithms and schemes for CB artifacts suppression in axial MDCT/CBCT.
Conclusions
With increasing importance of axial MDCT/CBCT in clinical and preclinical applications, this review article can update the community with in‐depth information and clarification on the latest progress in dealing with CB artifacts and thus increase clinical/preclinical confidence.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Transcranial transmission of ultrasound is increasingly used in a variety of clinical and research applications, including high intensity ablation, opening the blood brain barrier, and neural ...stimulation. Numerical simulations of ultrasound propagation in the head are used to enable effective transcranial focusing and predict intracranial fields. Such simulations require maps of the acoustic properties of the head, which can be derived from clinical CT images. However, the spatial resolution of these images is typically coarser than the scale of heterogeneities within the skull bone, which are known to exert a major influence on ultrasound propagation. In the present work, the impact of image related homogenisation on transcranial transmission from a single element transducer is examined using a dataset of co-registered clinical resolution CT and micro-CT images of skull sections. Reference acoustic property maps are derived from micro-CT images of cortical bone tissue. The influence of imaging resolution is examined by progressively downsampling the segmented acoustic property maps, and through comparison with maps derived from co-registered clinical CT images. The influence of different methods of segmenting the bone volume from the clinical CT images, and for resampling the clinical and micro-CT data are also examined. Image related homogenisation is demonstrated to have a substantial effect on the transcranial transmission of ultrasound, resulting in underestimations of simulated transmission loss and time-of flight. Effects on time-of flight are due to the loss of the internal scattering microstructure of the skull, while changes in transmitted ultrasound amplitude are due to both loss of microstructure and other smoothing effects. Inflating the simulated attenuation coefficient of the skull layer reduces the error in transmitted pressure amplitude to around 40%, however this is unable to correct fully for errors in time of flight and the pressure distribution of the transmitted field.
Training data is crucial for any artificial intelligence model. Previous research has shown that various methods can be used to enhance and improve AI training data. Taking a step beyond previous ...research, this paper presents a method that uses AI techniques to generate CT training data, especially realistic, artificial, industrial 3D voxel data. This includes that material as well as realistic internal defects, like pores, are artificially generated. To automate the processes, the creation of the data is implemented in a 3D Data Generation, called SPARC (Synthetized Process Artificial Realistic CT data). The SPARC is built as a pipeline consisting of several steps where different types of AI fulfill different tasks in the process of generating synthetic data. One AI generates geometrically realistic internal defects. Another AI is used to generate a realistic 3D voxel representation. This involves a conversion from STL to voxel data and generating the gray values accordingly. By combining the different AI methods, the SPARC pipeline can generate realistic 3D voxel data with internal defects, addressing the lack of data for various applications. The data generated by SPARC achieved a structural similarity of 98% compared to the real data. Realistic 3D voxel training data can thus be generated. For future AI applications, annotations of various features can be created to be used in both supervised and unsupervised training.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Carbonate rocks are among the sedimentary systems which preserve information on the formation and diagenetic history expressed in its composition (distribution of its major rock-forming components ...(RFC). For estimating RFC proportions at the micro-scale, a simple counting of visible RFCs in thin sections using overlaid grids is a long-used, well-established technique. However, computer tomography (CT) analysis provides us with quantitative data in 3D at both the scale of the entire sample and a resolution defined by dimensions of the voxels at the micro-scale. The quantitative data expressed in Hounsfield units (HU) correlates with the density of RFCs. In this work statistical properties of CT-based data for selected freshwater carbonate samples from the Danube-Tisza Interfluve have been assessed using histograms and boxplots. Univariate statistical parameters characterize each sample. The maximum-likelihood method of mixture analysis has been adapted to recover and estimate the parameters of these subpopulations. Subpopulations have been defined in the form of overlapping intervals using statistical parameters gained (mean±2STD). Five major components have been defined: empty and partially or entirely filled pores by calcite, limestone micrite, dolomite micrite matrix and limonite saturated matrix.
Abstract Obstructive sleep apnoea syndrome (OSAS) is a breathing disorder in sleep developed as a consequence of upper airway anatomical characteristics and sleep-related muscle relaxation. ...Fluid-structure interaction (FSI) simulation was adopted to explain the mechanism of pharyngeal collapse and snoring. The focus was put on the velopharyngeal region where the greatest level of upper airway compliance was estimated to occur. The velopharyngeal tissue was considered in a way that ensures proper boundary conditions, at the regions where the tissue adheres to the bone structures. The soft palate with uvula was not cut out from the surrounding tissue and considered as an isolated structure. Both, soft palate flutter as well as airway narrowing have been obtained by 3D FSI simulations which can be considered as a step forward to explain snoring and eventual occlusion. It was found out that during the inspiratory phase of breathing, at given elastic properties of the tissue and without taking gravity into consideration, velopharyngeal narrowing due to negative suction pressure occurs. Furthermore, soft palate flutter as the main attribute of snoring was predicted during the expiratory phase of breathing. The evaluated flutter frequency of 17.8 Hz is in close correlation with the frequency of explosive peaks of sound that are produced in palatal snoring in inspiratory phase, as reported in literature.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A three-dimensional (3D) understanding of muscle attachment footprints became increasingly relevant for musculoskeletal modeling. The established method to project attachments as points ignores ...patient-specific individuality. Research focuses on investigating certain muscle groups rather than comprehensively studying all muscles spanning a joint. Therefore, we present a reliable method to study several muscle attachments in order to reconstruct the attachment sites in 3D based on CT imaging for future applications in musculoskeletal modeling. For the present feasibility study, 23 knee-related muscle attachments were CT-scanned postmortem from four nonadipose male specimens. For this, the specific muscle attachments were dissected and marked with a barium sulfate containing paint (60 g BaSO4 in 30 mL water and 10 mL acrylic paint). Subsequently, bone geometries and muscle attachments were reconstructed and evaluated from CT datasets. Bone morphology and footprint variations were studied. Exemplarily, variations were high for pes anserinus insertions (mean 56%) and the origins of M. biceps femoris (mean 54%). In contrast, the origins of the vastus muscles as well as the insertion of the Achilles tendon showed low variation (mean 9% and 13%, respectively). Most attachment sites showed variation exceeding the individuality of bone morphology. In summary, the present data were consistent with the few published studies of specific muscle footprints. Our data shed light on the high variability of muscle attachments, which need to be addressed when studying muscle forces and movements through musculoskeletal modeling. This is the first step to achieving a more profound understanding of muscle morphology to be utilized in numerical simulations.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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