A segmented vertebral column is one of the major innovations vertebrates. In mice and chicks – amniotes – a subpopulation of the somites, the sclerotome, is sole source of vertebral tissue. It is unclear, however, how applicable this amniote-based ‘canonical’ mechanism is across the vertebrates. In fact, the vast majority and diversity of vertebrates are not amniotes, but are members of ‘fish’ groups where there has been relatively little investigation into vertebral development. Indeed, there is great diversity in vertebra form throughout ‘fish’ groups and fossil evidence suggests that the components of the vertebra, the neural arches and the vertebral bodies, arose separately and that vertebrates have evolved multiple ways of building vertebral bodies. In teleosts fish, the vertebral bodies initially form as mineralised rings within the notochord sheath (chordacentra) and then secondarily, bone is deposited around this (perichordal centra and arches). Notochord cells (chordoblasts) have been implicated in chordacentrum mineralisation and patterning in zebrafish and Atlantic salmon, though the question of how the overtly unsegmented notochord could direct segmental mineralisation still remains. My project first aims to address this dual mechanism in the zebrafish model, by testing whether the chordoblasts can mineralise and pattern the chordacentra. The second aim is to elucidate the role of the sclerotome in teleost vertebral development. To do this, I explored CRISPR knock-in tools to label the sclerotome and used a Gal4 gene trap line to investigate sclerotome ablation. I characterised the chordacentra and chordoblasts in our model system and verified the specificity of a promoter as a chordoblast marker. With this promoter, I established a method to target the chordoblasts for KillerRed-induced phototoxicity. I demonstrated that intact chordoblasts are necessary for chordacentrum formation, but that vertebral arches are unaffected. Fused perichordal centra are still able to form, but the underlying sheath has a very different structure. This supports the ‘duality’ hypothesis that in teleosts the role of the sclerotome in vertebra formation is limited to the arches and perichordal centra, whereas the chordoblasts are responsible for the chordacentra.

Existing microstructure parameters of computed tomography (CT) are able to compute architectural properties of the bone from ex-situ and ex-vivo scans while they are highly affected by the issues of noise and low resolution when applied to clinical in-vivo imaging. A set of improvements of the standard workflow for the quantitative computation of micro-structure from clinical in-vivo scans is proposed in this thesis. Robust methods are proposed (1) for the calibration of density values, (2) the binarization into bone and marrow phase, (3) fuzzy skeletonization and (4) the calibration of the CT volumes in particular for the computation of micro-structural parameters. Furthermore, novel algorithms for the computation of rod-volume fraction with 3D rose diagrams and fractal approaches are proposed and the application of local texture operators to diffusion tensor imaging is proposed. Finally an existing computer program for the application in radiology departments, Structural Insight, was improved and largely extended. In particular the methods of the microstructural calibration, the fractal and the texture operators showed significant improvements of accuracy and precision for the prediction of fracture risk and the quantitative assessment of the progress of Alzheimer's disease, in comparison to existing state-of-the art methods. The methods were tested on artificial and in-vitro data and as well on real-world computed tomography and magnetic resonance imaging (MRI) studies. The proposed novel methods improve the computation of bone characteristics from in-vivo CT and MRI in particular if the methods are combined with each other. In consequence, this allows to assess more information from existing data or to conduct studies with less ray exposure and regarding the MRI method in shorter time than nowadays required.

This study examines the possible correlations between vertebral osteoporosis, spondylolysis, spondylolisthesis, Schmorl’s nodes, vertebral osteoarthritis, osteophytosis, and laminal spurs. Further, this study examines the effects of sex, age, ancestry, and occupation on the vertebral pathologies. A total of 238 individuals (54 African Americans and 184 randomly selected European Americans) from the William M. Bass Donated Skeletal Collection at the University of Tennessee, Knoxville, were analyzed. Vertebral pathologies and anomalies were assessed using visual morphometric scoring methods outlined in previous research. It is hypothesized that positive correlations exist between osteoporosis and other vertebral pathologies and a positive correlation exists between vertebral pathologies and strenuous occupations. It is also hypothesized that there is a difference in the prevalence of vertebral pathologies between European American and African American ancestries due to African Americans generally showing higher bone mineral density than European Americans (Aloia 2008). The results of this research demonstrate numerous relationships: females are correlated with more severe osteoarthritis, osteoporosis, and spondylolisthesis, while males correlate with Schmorl’s nodes; European Americans are correlated with osteoporosis, osteoarthritis, osteophytosis, and Schmorl’s nodes, while African Americans are correlated with laminal spurs; individuals 40 years or older are correlated with osteoporosis, osteoarthritis, Schmorl’s nodes, and laminal spurs; and lastly, labor intensive occupations (i.e., construction worker) are correlated with osteoarthritis, osteophytosis, and Schmorl’s nodes, all with p-values less than 0.05. The majority of the pathological conditions also correlate with each other, for example, osteoporosis and osteoarthritis. This research demonstrates how pathological conditions correlate with sociodemographic risk factors and with other pathological conditions, which can help with the identification process of skeletal remains in archaeological and forensic contexts.

Intervertebral disc (IVD) degeneration is strongly associated with back pain, and affects approximately 60% of the population by age 70. Furthermore, it has been suggested that this degeneration may play an important role in the initiation or perpetuation of vertebral fractures. Given that the IVD is a primary load-bearing structure in the spine, the change of intradiscal pressure (IDP) over time that accompanies disc degeneration provides a functional measure of the disease pathology. Studies show that both an overall decrease in IDP magnitude and changes in the spatial distribution of IDP are found with increasing levels of degeneration. Thus, the overall goal of this study was to determine the correlation between the spatial distributions of IDP, as measured along both mid-sagittal and mid-coronal paths, and a clinically feasible assessment of disc health. Disc degeneration was assessed non-invasively using quantitative computed tomography (QCT). A custom, electro-mechanical device was designed, manufactured and assembled to measure IDP distributions. The results indicated that the spatial distribution of IDP was most homogenous for the nucleus pulposus (NP) region regardless of load type and disc health grade. Mean IDP tended to be lowest in severely degenerated discs, consistent with earlier findings that axial loads in spinal columns with degenerated IVDs shift from the disc to the neural arch in both flexural and erect postures.

Seahorses, genus Hippocampus erectus, are subject to large and continuously-growing international trade. Concerns with the effects of trade on seahorse population worldwide have led to their international protection by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). In order to manage seahorse populations, we first need to understand their basic biology. The purpose of this project was to establish an energy budget for Hippocampus erectus from Tampa Bay, Florida. A total of 108 specimens were collected throughout Tampa Bay from 2004 to 2007 using 21.3 m offshore seines and 6.1 m otter trawls. Those specimens were utilized to determine different components of the energy budget: size at maturity, feeding and nutrition within a captive environment, and metabolic rate. Seahorses collected in the study ranged in size from 4 mm to 160 mm, and were 0 to 4 years in age. Conventional methods of aging fish could not be applied to this species. Instead, an alternative method that involved sectioning vertebrae and using Scanning Electron Microscopy (SEM) to enumerate age-specific marks on vertebra was employed. Age data were then paired against length-weight charts to estimate age by length and mass. Length-frequencies were segregated by sex and compared to the growth data. No sex-specific differences were found. Fish reared in captivity were also used for nutrition, respiration, excretion analysis. Hippocampus erectus in captivity were calculated to have a resting respiration rate of 85.9 microliter O2/g/h and an excretion rate of 0.48 mmol NH3/g/h. The viscera of H. erectus and Artemia spp. were broken into protein and lipid content by caloric composition. The overall percentage of protein per seahorse was 11% and 17% by lipid concentration. Overall the sum of energy cost of H. erectus accounted for 81% of the total energy ingested.

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This body of work investigates the contradictory aspects of human connections, which can serve as sources of solace as well as sources of sorrow. It particularly focuses on the dynamics of toxic relationships, highlighting how the allure of intense love is often intertwined with the potential for significant emotional distress. The purpose of this exploration is to show in my installation the dichotomy between deep affection and detrimental dependency, how profound emotions can lead to both self-discovery and self-destruction. The reflection is rooted in the examination of the fine line that exists between passionate attachment and harmful reliance.  This endeavor is not just a scholarly investigation but also a personal journey into the depths of human desire and its implications. By navigating this research through the lens of art, the objective is to contribute to the broader dialogue on the nature of emotional bonds and their impact on individuals.  The exploration presented here seeks to offer insights into the enriching yet destructive facets of love, inviting viewers and readers alike to reflect on their own experiences and perceptions of romantic relationships. Through this artistic inquiry, the intention is to illuminate the multifaceted experiences of love, drawing attention to the intricate balance between its empowering and detrimental effects on the human spirit.

Automated spine or vertebra detection and segmentation from CT images is a difficult task for several reasons. One of the reasons is unclear vertebra boundaries and indistinct boundaries between vertebra. Next reason is artifacts in images and high degree of anatomical complexity. This paper describes the design and implementation of vertebra detection and classification in CT images of cancer patients, which adds to the complexity because some of vertebrae are deformed. For the vertebra segmentation, the Otsu’s method is used. Vertebra detection is based on search of borders between individual vertebra in sagittal planes. Decision trees or the generalized Hough transform is applied for the identification whereas the vertebra searching is based on similarity between each vertebra model shape and planes of CT scans.

In this doctoral thesis, the design of algorithms enabling the implementation of a fully automatic system for vertebrae segmentation in 3D computed tomography (CT) image data of possibly incomplete spines, in patients with bone metastases and vertebral compressions is presented. The proposed algorithm consists of several fundamental problems: spine detection and its axis determination, individual vertebra localization and identification (labeling), and finally, precise segmentation of vertebrae. The detection of the spine, specifically identifying its ends, and determining the course of the spinal canal, combines several advanced methods, including deep learning-based approaches. A novel growing circle method has been designed for tracing the spinal cord canal. Further, the innovative spatially variant filtering of brightness profiles along the spine axis leading to intervertebral disc localization has been proposed and implemented. The discs thus obtained are subsequently identified via comparing the tested vertebrae and model of vertebrae provided by a machine-learning process and optimized by dynamic programming. The final vertebrae segmentation is provided by the deformation of the complete-spine intensity model, utilizing a proposed multilevel registration technique. The complete proposed algorithm has been validated on testing databases, including also publicly available datasets. This way, it has been proven that the newly proposed algorithms provide results at least comparable to other author’s algorithms, and in some cases, even better. The main strengths of the algorithms lie in high reliability of the results and in the robustness to even strongly distorted vertebrae of oncological patients and to the occurrence of artifacts in data; moreover, they are capable of identifying the vertebra labels even in incomplete spinal CT scans. The strength is also in the complete automation of the processing and in its relatively low computational complexity enabling implementation on standard PC hardware. The system for fully automatic localization and labeling of distorted vertebrae in possibly incomplete spinal CT data is presented in this doctoral thesis. The design of algorithms enabling the implementation utilizes several novel approaches, which were presented at international conferences and published in the journal Jakubicek et al. (2020). Based on the results of the experimental validation, the proposed algorithms seem to be routinely usable and capable of providing fully acceptable input data (identified and precisely segmented vertebrae) as needed in the subsequent automatic spine bone lesion analysis.

A idade óssea é uma informação importante para o diagnóstico de anomalias ósseas e identificação dos estágios de desenvolvimento na pediatria, endocrinologia e ortodontia, assim como na estimação de idade na área forense. A idade óssea é obtida pela análise de qualquer osso ou conjunto de ossos por meio de radiografias da região de interesse. Este trabalho apresenta uma metodologia composta por duas fases. A primeira fase trata do processamento de imagem, responsável pela segmentação e extração de características de telerradiografias em norma lateral. A segunda fase é responsável pela estimação da idade óssea, que propõe um estudo para correlacionar o polinômio extraído da concavidade inferior da terceira vértebra com a idade óssea por meio de redes neurais artificiais. Para a média dos resultados da primeira fase, os valores encontrados foram 82,39% de precisão, 91,70% de exatidão e 8,30% de erro. Baseado nestes resultados concluiu-se que a metodologia é eficaz para a segmentação dos ossos das cervicais, entretanto como algumas estruturas não devem ser consideradas, a segmentação foi influenciada pela contribuição dos falsos positivos, que nas imagens analisadas são segmentos de ossos da parte posterior das cervicais. Em contrapartida, para a segunda fase os resultados validaram o uso do polinômio em métodos de estimação, que pode ser utilizado de forma direta (coeficientes do polinômio) ou indireta (área e máxima altura da concavidade), comprovando que ele contribui no aumento da correlação quando utilizado em conjunto com outras características. Para ambos os gêneros a correlação atingiu valores em torno de 0,97, com erro médio absoluto de 0,4 anos e sem diferenças estatisticamente significativas pelo T-Student com nível de significância de 5%. Portanto concluiu-se que a metodologia apresenta resultados expressivos, respeitando a tolerância dos métodos clássicos. / Bone age is important information for the diagnosis of bone anomalies and identification of developmental stages in pediatrics, endocrinology and orthodontics as well in the age estimation in the forensic field. Bone age is obtained by analysis of any bone or group of bones through of radiographs the region of interest. This paper presents a methodology that consists of two phases. The first phase deals with image processing, responsible for segmentation and feature extraction of lateral cephalograms. The second phase is responsible for bone age estimation, which proposes a study to correlate the polynomial extracted from bottom concavity of the third vertebra with bone age using artificial neural networks. The average of first phase results was 82.39% of precision, 91.70% of accuracy and 8.30% of error. Based on these results it was concluded that the method is effective for the segmentation of the cervical bone, however, since some structures should not be considered, the segmentation was influenced by the contribution of false positives, that in the images analyzed are bones segments from the back of the cervical. In contrast, for the second phase the results validated the use of polynomial in estimation methods that can be used directly (polynomial coefficients) or indirect (area and maximum height of concavity), proving that it contributes in increasing the correlation when used together with other features. For both genders the correlation reached values around 0.97, with a mean absolute error of 0.4 years and no statistically significant differences by T-Student with a significance level of 5%. Therefore it was concluded that the methodology shows significant results, respecting the tolerance of the classical methods.