The Role of Transient Vibration of the Skull on Concussion

Concussion is a traumatic brain injury usually caused by a direct or indirect blow to the head that affects brain function. The maximum mechanical impedance of the brain tissue occurs at 450±50 Hz and may be affected by the skull resonant frequencies. After an impact to the head, vibration resonance of the skull damages the underlying cortex. The skull deforms and vibrates, like a bell for 3 to 5 milliseconds, bruising the cortex. Furthermore, the deceleration forces the frontal and temporal cortex against the skull, eliminating a layer of cerebrospinal fluid. When the skull vibrates, the force spreads directly to the cortex, with no layer of cerebrospinal fluid to reflect the wave or cushion its force. To date, there is few researches investigating the effect of transient vibration of the skull. Therefore, the overall goal of the proposed research is to gain better understanding of the role of transient vibration of the skull on concussion. This goal will be achieved by addressing three research objectives. First, a MRI skull and brain segmentation automatic technique is developed. Due to bones’ weak magnetic resonance signal, MRI scans struggle with differentiating bone tissue from other structures. One of the most important components for a successful segmentation is high-quality ground truth labels. Therefore, we introduce a deep learning framework for skull segmentation purpose where the ground truth labels are created from CT imaging using the standard tessellation language (STL). Furthermore, the brain region will be important for a future work, thus, we explore a new initialization concept of the convolutional neural network (CNN) by orthogonal moments to improve brain segmentation in MRI. Second, the creation of a novel 2D and 3D Automatic Method to Align the Facial Skeleton is introduced. An important aspect for further impact analysis is the ability to precisely simulate the same point of impact on multiple bone models. To perform this task, the skull must be precisely aligned in all anatomical planes. Therefore, we introduce a 2D/3D technique to align the facial skeleton that was initially developed for automatically calculating the craniofacial symmetry midline. In the 2D version, the entire concept of using cephalometric landmarks and manual image grid alignment to construct the training dataset was introduced. Then, this concept was extended to a 3D version where coronal and transverse planes are aligned using CNN approach. As the alignment in the sagittal plane is still undefined, a new alignment based on these techniques will be created to align the sagittal plane using Frankfort plane as a framework. Finally, the resonant frequencies of multiple skulls are assessed to determine how the skull resonant frequency vibrations propagate into the brain tissue. After applying material properties and mesh to the skull, modal analysis is performed to assess the skull natural frequencies. Finally, theories will be raised regarding the relation between the skull geometry, such as shape and thickness, and vibration with brain tissue injury, which may result in concussive injury

Applications and Experiences of Quality Control

The rich palette of topics set out in this book provides a sufficiently broad overview of the developments in the field of quality control. By providing detailed information on various aspects of quality control, this book can serve as a basis for starting interdisciplinary cooperation, which has increasingly become an integral part of scientific and applied research

Coherent methods in the X-ray sciences

X-ray sources are developing rapidly and their coherent output is growing extremely rapidly. The increased coherent flux from modern X-ray sources is being matched with an associated rapid development in experimental methods. This article reviews the literature describing the ideas that utilise the increased brilliance from modern X-ray sources. It explores how ideas in coherent X-ray science are leading to developments in other areas, and vice versa. The article describes measurements of coherence properties and uses this discussion as a base from which to describe partially-coherent diffraction and X-ray phase contrast imaging, with its applications in materials science, engineering and medicine. Coherent diffraction imaging methods are reviewed along with associated experiments in materials science. Proposals for experiments to be performed with the new X-ray free-electron-lasers are briefly discussed. The literature on X-ray photon correlation spectroscopy is described and the features it has in common with other coherent X-ray methods are identified. Many of the ideas used in the coherent X-ray literature have their origins in the optical and electron communities and these connections are explored. A review of the areas in which ideas from coherent X-ray methods are contributing to methods for the neutron, electron and optical communities is presented.Comment: A review articel accepted by Advances in Physics. 158 pages, 29 figures, 3 table

Development of Optical Devices for Digital Medicine

Department of Biomedical EngineeringAdvances of technology have made a revolution that interconnects industrial devices and fuses the boundaries of digital, physical and biological spaces. These technologies such as cloud computing, 3D printing technology, big data, internet of things (IOT), artificial intelligence (AI), and maturity of system integrations have been improved every year, changing our daily life quickly in intelligent and convenient ways. In this days, these explosions of technology, changing the way we live and think, is referred to 4th industrial revolution. As we know, every industry is affected by the new waves of technologies, digitalization and connectivity, and the biomedical or medical field is no exception. Healthcare fields have benefited mostly from recent technical improvements, revolutionizing the medical systems in many terms in cost-effective ways. Particularly, ???digital medicine??? has been recently came into the limelight as one of the uprising fields. In digital medicine, traditional medical devices and diagnostic programs have become miniaturized, digitalized, and automated. As taking advantages of digital medicine, specific fields related to digital pathology, point-of-care (POC) diagnostics, and application of deep learning or machine learning technologies have shown the great potentials not only in biomedical academia but also in the revenues of their markets. It allows to connect devices, hospital equipment, and to accelerate efficiencies in health service such as diagnosis, and to reduce the cost of services. Moreover, interconnection between advanced technologies has been improved the access of healthcare to the places where hospital or medical services are limited. Furthermore, artificial intelligence has shown promising results related to disease screening especially using medical images. Although fields in digital medicine are prospering, still there are limitations that needs to be overcome in order to provide further advanced health services to patients in the various situations. In digital pathology, improvements of microscopic technologies, internets, and storage capabilities have reduced the time-consuming processes. The simple transformation of microscopic image to digital have successfully alternated many limitations in the analogue histopathology workflow to efficient and cost saving ways. However, tissue staining is currently referred as one of the bottleneck that makes workflow still lengthy, labor-intensive, and costly. In the POC diagnostic fields, various digitalized portable smartphone-based diagnostic devices have been introduced as alternatives to conventional medical services. These devices have provided the quality assurance of diagnostics by taking advantages of sharing, and quantitative analysis of digital information. However, most of these works have been focused on replacing diagnostic process which mostly done in laboratory settings. As medical imaging devices and trained clinicians or practitioners are limited, there are also high demands on clinical imaging-based diagnostics in developing countries. In this thesis, computational microscope using patterned NIR illumination was developed for label-free quantitative differential phase tissue imaging to bypass the staining process of the pathology workflow. This system overcame the limitations found in the conventional quantitative differential phase contrast in a LED array microscope, allowing to captured light scattering and absorbing specimen while maintaining weak object approximation. Moreover, portable endoscope system was developed integrating the additive production technologies (3D printing), ICT, and optics for POC diagnostics. This innovative POC endoscope demonstrated comparable imaging capability to that of commercialized clinical endoscope system. Furthermore, deep learning and machine learning models have been trained and applied to each devices, respectively. Generative adversarial network (GAN) was applied to our NIR-based QPI system to virtually stain the label-free QPI which look comparable to image that is captured from bright field microscope using labeled tissue. Lastly, POC automated cervical cancer screening system was developed utilizing smartphone-based endoscope system as well as training the machine learning algorithm. 3-5% of acetic acid was applied to the suspicious lesion and its reaction was captured before and after application using smartphone endoscope. This screening system enables to extract the features of cancers and informs the possibility of cancer from endoscopic images.clos

Examining Uptake of Nanomaterials by Eukaryotic Cells with Digital Image Cytometry

Due to their small size and related interesting properties, artificial nanoma-terials are utilized for a great number of biological and medical applications. Cell entry routes, intracellular trafficking and processing of nanoparticles, which determine their fate, efficiency, and toxicity, are depending on various parameters of the specific nanomaterial, such as size, surface charge, surface chemistry and elasticity. Nanoparticle-cell interactions are typically elucidated by means of fluorescence microscopy. Cell functions can be observed by a multiplicity of commercially available probes. For the quantification of cell features from images (image cytometry), computer-based algorithms are favoured to avoid bias introduced by the subjective perception of the observer. By applying high throughput microscopy in combination with digital image cytometry the screening of high numbers of cells is made possible. With the large quantity of obtained data, cell populations can be identified and, in general, results that are statistically meaningful are obtained. In the first part of this work this method is applied in order to examine the cellular responses upon exposure to plasmonic poly(methacrylic acid)-coated gold nanoparticles (Au NPs) with respect to morphology and viability of human endothelial and epithelial cells (HUVECs and HeLa cells). Au NPs of 4-5 nm size were chosen which had been thoroughly characterized in terms of their physico-chemical parameters. These particles bear interesting properties for biomedical applications and, for several years, have been in the focus of research. In this work significant impacts on mitochondrial and lysosomal morphology upon exposure to the Au NPs are reported. The alteration of the structure of the cytoskeleton and a dramatically reduced proliferation are described. Interestingly, the smallest dose inducing the described cellular responses was of one or two magnitudes lower than those, where acute cytotoxicity and an increase in the production of reactive oxygen species (ROS) were observed. In the second part the process of endocytosis of polymer capsules is examined. These systems are seen as a promising tool for intracellular cargo delivery and release. After lipid raft-mediated phagocytosis, the capsules are transferred from the neutral extracellular medium to increasingly acidic intracellular vesicles. By embedding a pH-sensitive fluorescent dye into the cavity of the capsule the uptake process and the associated acidification can be monitored time-dependently. It is demonstrated that the kinetic of the acidification process strongly depends on the stiffness of the capsules. Soft particles with minor stiffness are transported faster into lysosomal structures than stiffer ones. Additionally, these sensor particles are used to confirm the importance of the V1G1-subunit of the vacuolar ATPase being responsible for vesicle acidification

Detection and description of pulmonary nodules through 2D and 3D clustering

Precise 3D automated detection, description and classification of pulmonary nodules offer the potential for early diagnosis of cancer and greater efficiency in the reading of computerised tomography (CT) images. CT scan centres are currently experiencing high loads and experts shortage, especially in developing countries such as Iraq where the results of the current research will be used. This motivates the researchers to address these problems and challenges by developing automated processes for the early detection and efficient description of cancer cases. This research attempts to reduce workloads, enhance the patient throughput and improve the diagnosis performance. To achieve this goal, the study selects techniques for segmentation, classification, detection and implements the best candidates alongside a novel automated approach. Techniques for each stage in the process are quantitatively evaluated to select the best performance against standard data for lung cancer. In addition, the ideal approach is identified by comparing them against other works in detecting and describing pulmonary nodules. This work detects and describes the nodules and their characteristics in several stages: automated lung segmentation from the background, automated 2D and 3D clustering of vessels and nodules, applying shape and textures features, classification and automatic measurement of nodule characteristics. This work is tested on standard CT lung image data and shows promising results, matching or close to experts’ diagnosis in the nodules number and their features (size/volume, location) and in terms the accuracy and automation. It also achieved a classification accuracy of 98% and efficient results in measuring the nodules’ volume automatically

Protein Structure

Since the dawn of recorded history, and probably even before, men and women have been grasping at the mechanisms by which they themselves exist. Only relatively recently, did this grasp yield anything of substance, and only within the last several decades did the proteins play a pivotal role in this existence. In this expose on the topic of protein structure some of the current issues in this scientific field are discussed. The aim is that a non-expert can gain some appreciation for the intricacies involved, and in the current state of affairs. The expert meanwhile, we hope, can gain a deeper understanding of the topic