We develop a formal procedure for the automated recognition of rational and elliptic curves in medical and astronomical images. The procedure is based on the extension of the Hough transform concept to the definition of Hough transform of special classes of algebraic curves. We first introduce a catalogue of curves that satisfy the conditions to be automatically extracted from an image and the recognition algorithm, then we illustrate the power of this method to identify skeleton profiles in clinical X-ray tomography maps and front ends of solar eruptions in astronomical images provided by the NASA solar dynamics observatory satellite
PurposeIn amyotrophic lateral sclerosis, functional alterations within the brain have been intensively assessed, while progression of lower motor neuron damage has scarcely been defined. The aim of the present study was to develop a computational method to systematically evaluate spinal cord metabolism as a tool to monitor disease mechanisms.MethodsA new computational three-dimensional method to extract the spinal cord from 18F-FDG PET/CT images was evaluated in 30 patients with spinal onset amyotrophic lateral sclerosis and 30 controls. The algorithm identified the skeleton on the CT images by using an extension of the Hough transform and then extracted the spinal canal and the spinal cord. In these regions, 18F-FDG standardized uptake values were measured to estimate the metabolic activity of the spinal canal and cord. Measurements were performed in the cervical and dorsal spine and normalized to the corresponding value in the liver.ResultsUptake of 18F-FDG in the spinal cord was significantly higher in patients than in controls (p < 0.05). By contrast, no significant differences were observed in spinal cord and spinal canal volumes between the two groups. 18F-FDG uptake was completely independent of age, gender, degree of functional impairment, disease duration and riluzole treatment. Kaplan-Meier analysis showed a higher mortality rate in patients with standardized uptake values above the fifth decile at the 3-year follow-up evaluation (log-rank test, p < 0.01). The independence of this value was confirmed by multivariate Cox analysis.ConclusionOur computational three-dimensional method enabled the evaluation of spinal cord metabolism and volume and might represent a potential new window onto the pathophysiology of amyotrophic lateral sclerosis.
We describe a computational approach for the automatic recognition and classification of atomic species in scanning tunnelling microscopy images. The approach is based on a pipeline of image processing methods in which the classification step is performed by means of a Fuzzy Clustering algorithm. As a representative example, we use the computational tool to characterize the nanoscale phase separation in thin films of the Fe-chalcogenide superconductor FeSex Te1-x , starting from synthetic data sets and experimental topographies. We quantify the stoichiometry fluctuations on length scales from tens to a few nanometres.
It has been recently proved that the computational analysis of X-ray Computed Tomography (CT) images allows clinicians to assess the alteration of compact bone asset due to hematological diseases. HT-BONE implements a new method, based on an extension of the Hough transform (HT) to a wide class of algebraic curves, for accurately measuring global and regional geometric properties of trabecular and compact bone districts. In the case of CT/PET analysis, the segmentation of the CT images provides masks for Positron Emission Tomography (PET) data, extracting the metabolic activity in the region surrounded by compact bone tissue. HT-BONE offers an intuitive, user-friendly, Matlab-based Graphical User Interface (GUI) for all input/output procedures and the automatic managing of the segmentation process also from non-expert users: the CT/PET data can be loaded and browsed easily and the only pre-preprocessing required from the user is the drawing of Regions Of Interest (ROIs) around the bone districts under consideration. For each bone district, specific families of curves, whose reliability has been already tested in previous works, is automatically selected for the recognition task via HT. As output, the software returns masks of the segmented compact bone regions, images of the Standard Uptake Values (SUV) in the masked regions of PET slices, and the values of the parameters in the curve equations utilized in the HT procedure. This information can be used for all pathologies and clinical conditions for which the alteration of the compact bone asset or bone marrow distribution plays a crucial role.
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