Talita Perciano

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Vibro-acoustography (VA) is an imaging modality that produces an image of the mechanical response of an object to a localized dynamic radiation force of an ultrasound field. This technique has been studied and used in clinical applications as to image calcification in breast tissue and arteries. This paper presents the application of restoration algorithms(More)
The best ebooks about Introduction To Image Processing Using R Learning By Examples that you can get for free here by download this Introduction To Image Processing Using R Learning By Examples and save to your desktop. This ebooks is under topic such as introduction to image processing using r learning by examples introduction to image processing using r(More)
This paper presents a processing chain to combine a CosmoSkyMed (CSK) image and a TerraSAR-X (TSX) image. After registration and calibration steps, processing at different levels is studied: pixel level for the detection of stable features and joint filtering, primitive level for stability analysis and object level (like roads) for joint interpretation.
A ridge linking algorithm and its application to plant root images is presented. The idea is an improvement of an edge linking algorithm where we explore local directional information. The experimental results show that we obtain good connections between ridge segments which tends to maintain the connectivity of structures like plant roots.
Fibers provide exceptional strength-to-weight ratio capabilities when woven into ceramic composites, transforming them into materials with exceptional resistance to high temperature, and high strength combined with improved fracture toughness. Microcracks are inevitable when the material is under strain, which can be imaged using synchrotron X-ray computed(More)
Vibro-acoustography (VA) is a medical imaging method based on the difference-frequency generation produced by the mixture of two focused ultrasound beams. VA has been applied to different problems in medical imaging such as imaging bones, microcalcifications in the breast, mass lesions, and calcified arteries. The obtained images may have a resolution of(More)
Markov Random Field (MRF) algorithms are powerful tools in image analysis to explore contextual information of data. However, the application of these methods to large data means that alternative approaches must be found to circumvent the NP-hard complexity of the MRF optimization. We introduce a MRF-based framework that overcomes this issue by using graph(More)
Three-dimensional (3D) micro-tomography (µ-CT) has proven to be an important imaging modality in industry and scientific domains. Understanding the properties of material structure and behavior has produced many scientific advances. An important component of the 3D µ-CT pipeline is image partitioning (or image segmentation), a step that is used to separate(More)