Publications (2)0 Total impact
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ABSTRACT: Bone Histomorphometry is an important analysis in preventing and treatment of cancer and osteoporosis patients, providing quantitative information about the bone structure. X-Ray Micro-Computer Tomography is a non-invasive and non-destructive imaging technique, with a high space resolution that enables magnified images. In the histomorphometric analysis of such images, it is possible to use filters and binarization, nevertheless these techniques may cause loss of information. In this paper we describe the usage of Artificial Neural Networks (ANNs) in Microtomography X-Ray imaging bone recognition as a part of a histomorphometric analysis research with raw images obtained at the Synchrotron Radiation for Medical Physics (SYRMEP) beamline of the ELETTRA Laboratory at Trieste, Italy. A Multilayer Perceptron Model for the ANNs with Error Back-Propagation and supervised learning has been used in the recognition task. The classification of bone subimages yielded a Receiver Operating Characteristic Curve with an area under curve of 1.000, which means that the ANN is able to distinguish successfully the bone mass. The images obtained are also depicted herein. The quality and characteristics of the X-Ray Computer Microtomography are compatible with the ANN-based proposed methodology, avoiding the loss of information due to image manipulation.IEEE Nuclear Science Symposium conference record. Nuclear Science Symposium 01/2008;
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ABSTRACT: In this work, we intend to relate the mineral to non-mineral bone scattering intensity ratio with the bone-mineral density (BMD) reduction. In this way, EDXRD can be a novel technique to measure BMD loss in function of the mineral and non-mineral scattering intensity. The scattering profiles were obtained at Laboratório Nacional de Luz Síncrotron (LNLS) at the X-ray diffraction beamline XD2. A double-crystal Si(111) pre-monochromator, upstream of the beamline, was used to select a small energy bandwidth (Δλ/λ≈10−4) at 11keV. The sample holder has a circle depression in the center to contain a range of bone and fat mixture ratios. The mixture consists of powdered cortical bone and fat, which together simulate in vivo bone. The diffraction patterns were carried out with 0.5mm slits after and behind of the sample holder. The data were collected in 0.05° increments every 0.5s. EDXRD results show an indication of different bone densities may be distinguished which suggested that X-ray coherent scattering technique may have a role in monitoring changes in BMD via changes in the related scattering intensity of mineral and non-mineral bone. The main aim of the Synchrotron Radiation for MEdical Physics (SYRMEP) project at the ELETTRA is the investigation and the development of innovative techniques for medical imaging. The beamline provides, at a distance of about 23m from the source, a monochromatic, laminar section X-ray beam with a maximum area of about 160×5mm2 at 20keV. The monochromator, that covers the entire angular acceptance of the beamline, is based on a double-Si (111) crystal system working in Bragg configuration. A micrometric vertical and horizontal translation stage allows the positioning and scanning of the sample with respect to the stationary beam. In this case, the detector is kept stationary in front of the beam, while the object is rotated in discrete steps in front of it. At each rotation, a projection is acquired. A goniometric double-cradle system is used to adjust the rotation axis, which must be orthogonal with respect to the detector plane in transmission computed tomography (CT). The samples consisted of a 8mm cube of bovine bone surrounded of a cartilage interface. High-resolution images of the trabecular structure were obtained by means a 16-bit CCD camera, 2048×2048 pixels, 14μm pixel size (maximum spatial resolution: 25μm).Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment - NUCL INSTRUM METH PHYS RES A. 01/2007; 579(1):318-321.
Rio de Janeiro State UniversityRio de Janeiro, Rio de Janeiro, Brazil