Registration and Segmentation of Multimodality Images for Post Processing of Skeleton in Preclinical Oncology Studies

Advancements in medical imaging techniques provide biomedical researchers with quality anatomical and functional information inside preclinical subjects in the fields of cancer, osteopathic, cardiovascular, and neurodegenerative research. The throughput of the preclinical imaging studies is a critical factor which determines the pace of small animal medical research. The time involved in manual analysis of large amount of imaging data prior to data interpretation by the researcher, limits the number of studies in a time frame. In the proposed solution, an automated image segmentation method was used to segment individual vertebrae in mice. Individual vertebrae of MOBY atlas were manually segmented and registered to the CT data. The PET activity for L1-L5 vertebrae was measured by applying the CT registered atlas vertebrae ROI. The algorithm was tested on three datasets from a PET/CT bone metastasis study using 18F-NaF radiotracer. The algorithm was found to reduce the analysis time threefold with a potential to further reduce the automated analysis time by use of computer system with better specification to run the algorithm. The manual analysis value can vary each time the analysis is performed and is dependent on the individual performing the analysis. Also the error percent was recorded and showed an increasing trend as the analysis moves down the spine from skull to caudal vertebrae. This method can be applied to segment the rest of the bone in the CT data and act as the starting point for the registration of the soft tissues

Imagen hiperespectral de fluorescencia aplicada al estudio de tejidos vegetales

Treballs Finals de Grau de Química, Facultat de Química, Universitat de Barcelona, Any: 2018, Tutores: Anna de Juan Capdevila, Mónica Marro SánchezPlant tissues have natural fluorophores on their structure. When plants are exposed to an environmental stress, plant morphology, structural elements and content of fluorophores may vary. Three population of Oryza Sativa (rice) samples grew under control and stress conditions (watered with cadmium 50 μM and 1000 μM solutions). Fluorescence imaging allowed monitoring natural fluorophores such as chlorophylls or lignins in leave tissues. The information from fluorescence imaging was interpreted by the chemometric tool multivariate curve resolution alternating least squares (MCR – ALS) method which provides the pure fluorescence signatures and distribution maps of the fluorophores presents in the plants analyzed. Plants exposed to cadmium were more yellow indicating a lower concentration of chlorophylls. In leaves cross-sections, biological structures seem to be weaker than in non-contaminated plants. The leaf length also decreased in Cd-exposed populations. The fluorescence signatures and distribution maps of three types of chlorophyll and two lignin compounds were resolved. The use of fluorescence imaging techniques combined with chemometric tools are useful to obtain relevant biological, morphological and chemical information about compounds presents in plant tissues

Three-dimensional anatomical atlas of the human body

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsAnatomical atlases allow mapping the anatomical structures of the human body. Early versions of these systems consisted of analogic representations with informative text and labelled images of the human body. With the advent of computer systems, digital versions emerged and the third dimension was introduced. Consequently, these systems increased their efficiency, allowing more realistic visualizations with improved interactivity. The development of anatomical atlases in geographic information systems (GIS) environments allows the development of platforms with a high degree of interactivity and with tools to explore and analyze the human body. In this thesis, a prototype for the human body representation is developed. The system includes a 3D GIS topological model, a graphical user interface and functions to explore and analyze the interior and the surface of the anatomical structures of the human body. The GIS approach relies essentially on the topological characteristics of the model and on the kind of available functions, which include measurement, identification, selection and analysis. With the incorporation of these functions, the final system has the ability to replicate the kind of information provided by the conventional anatomical atlases and also provides a higher level of functionality, since some of the atlases limitations are precisely features offered by GIS, namely, interactive capabilities, multilayer management, measurement tools, edition mode, allowing the expansion of the information contained in the system, and spatial analyzes

Three-dimensional histological specimen preparation for accurate imaging and spatial reconstruction of the middle and inner ear

PURPOSE:    This paper presents a highly accurate cross-sectional preparation technique. The research aim was to develop an adequate imaging modality for both soft and bony tissue structures featuring high contrast and high resolution. Therefore, the advancement of an already existing microgrinding procedure was pursued. The central objectives were to preserve spatial relations and to ensure the accurate three-dimensional reconstruction of histological sections. METHODS:    Twelve human temporal bone specimens including middle and inner ear structures were utilized. They were embedded in epoxy resin, then dissected by serial grinding and finally digitalized. The actual abrasion of each grinding slice was measured using a tactile length gauge with an accuracy of one micrometre. The cross-sectional images were aligned with the aid of artificial markers and by applying a feature-based, custom-made auto-registration algorithm. To determine the accuracy of the overall reconstruction procedure, a well-known reference object was used for comparison. To ensure the compatibility of the histological data with conventional clinical image data, the image stacks were finally converted into the DICOM standard. RESULTS:    The image fusion of data from temporal bone specimens’ and from non-destructive flat-panel-based volume computed tomography confirmed the spatial accuracy achieved by the procedure, as did the evaluation using the reference object. CONCLUSION:    This systematic and easy-to-follow preparation technique enables the three-dimensional (3D) histological reconstruction of complex soft and bony tissue structures. It facilitates the creation of detailed and spatially correct 3D anatomical models. Such models are of great benefit for image-based segmentation and planning in the field of computer-assisted surgery as well as in finite element analysis. In the context of human inner ear surgery, three-dimensional histology will improve the experimental evaluation and determination of intra-cochlear trauma after the insertion of an electrode array of a cochlear implant system

Co-registration of optoacoustic tomography and magnetic resonance imaging data from murine tumour models.

As optoacoustic tomography (OT) emerges as a mainstream pre-clinical imaging modality, understanding the relationship between optoacoustic and other imaging biomarkers in the context of the underlying tissue biology becomes vitally important. Complementary insight into tumour vasculature and hypoxia can be gained using OT alongside magnetic resonance imaging (MRI)-based techniques. To evaluate the relationship between these metrics and the relative performance of the two modalities in assessment of tumour physiology, co-registration of their output imaging data is required. Unfortunately, this poses a significant challenge due to differences in animal positioning during imaging. Here, we present an integrated framework for registration of OT and MR image data in mice. Our framework combines a novel MR animal holder, to improve animal positioning during imaging, and a landmark-based software co-registration algorithm. We demonstrate that our protocol significantly improves registration of both body and tumour contours between these modalities, enabling more precise multi-modal tumour characterisation

Cloud-based Medical Image Collection Database with Automated Annotation

Typical medical image annotation systems use manual annotation or complex proprietary software such as computer-assisted-diagnosis. A more objective approach is required to achieve generalised Content Based Image Retrieval (CBIR) functionality. The Automated Medical Image Collection Annotation (AMICA) toolkit described here addresses this need. A range of content analysis functions are provided to tag images and image regions. The user uploads a DICOM file to an online portal and the software finds and displays images that have similar characteristics. AMICA has been developed to run in the Microsoft cloud environment using the Windows Azure platform, to cater for the storage requirements of typical large medical image databases

Lumbar Model Generator:a tool for the automated generation of a parametric scalable model of the lumbar spine

Low back pain is a major cause of disability and requires the development of new devices to treat pathologies and improve prognosis following surgery. Understanding the effects of new devices on the biomechanics of the spine is crucial in the development of new effective and functional devices. The aim of this study was to develop a preliminary parametric, scalable and anatomically accurate finite-element model of the lumbar spine allowing for the evaluation of the performance of spinal devices. The principal anatomical surfaces of the lumbar spine were first identified, and then accurately fitted from a previous model supplied by S14 Implants (Bordeaux, France). Finally, the reconstructed model was defined according to 17 parameters which are used to scale the model according to patient dimensions. The developed model, available as a toolbox named the lumbar model generator, enables generating a population of models using subject-specific dimensions obtained from data scans or averaged dimensions evaluated from the correlation analysis. This toolbox allows patient-specific assessment, taking into account individual morphological variation. The models have applications in the design process of new devices, evaluating the biomechanics of the spine and helping clinicians when deciding on treatment strategies.</jats:p