5 research outputs found
Sparse Representation of Deformable 3D Organs with Spherical Harmonics and Structured Dictionary
This paper proposed a novel algorithm to sparsely represent a deformable surface (SRDS) with low dimensionality based on spherical harmonic decomposition (SHD) and orthogonal subspace pursuit (OSP). The key idea in SRDS method is to identify the subspaces from a training data set in the transformed spherical harmonic domain and then cluster each deformation into the best-fit subspace for fast and accurate representation. This algorithm is also generalized into applications of organs with both interior and exterior surfaces. To test the feasibility, we first use the computer models to demonstrate that the proposed approach matches the accuracy of complex mathematical modeling techniques and then both ex vivo and in vivo experiments are conducted using 3D magnetic resonance imaging (MRI) scans for verification in practical settings. All results demonstrated that the proposed algorithm features sparse representation of deformable surfaces with low dimensionality and high accuracy. Specifically, the precision evaluated as maximum error distance between the reconstructed surface and the MRI ground truth is better than 3 mm in real MRI experiments
Statistical Model-Based Corneal Reconstruction
Precise measurements of corneal layer thickness are required to treat, evaluate risk of, and determine the progression of pathologies within the eye. The thickness measurements are typically acquired as 2d images, known as tomograms, from an optical coherence tomography (OCT) system. With the creation of ultra-high resolution OCT (UHROCT), there is active research in precisely measuring, in vivo, previously unresolvable corneal structures at arbitrary locations within the cornea to determine their relationship with corneal health.
In order to obtain arbitrary corneal thickness measurements, existing reconstruction techniques require the cornea to be densely sampled so that a 3d representation can be interpolated from a stack of tomograms. Unfortunately, tomogram alignment relies solely on image properties such as pixel intensity, and does not constrain the reconstruction to corneal anatomy. Further, the reconstruction method cannot properly compensate for eye-motion. The deficiencies due to eye-motion are exacerbated due to the amount of time required in a single imaging session to acquire a sufficient number of tomograms in the region of interest.
The proposed methodology is the first to incorporate models of the anatomy and the imaging system to address the limitations of existing corneal reconstruction methods. By constructing the model in such a way as to decouple anatomy from the imaging system, it becomes less computationally expensive to estimate model parameters. The decoupling provides an iterative methodology that can allow additional constraints to be introduced in the future. By combining sparsely sampled UHROCT measurements with a properly designed corneal model, reconstruction allows researchers to determine corneal layer thicknesses at arbitrary positions in both sampled and unsampled regions.
The proposed methodology demonstrates an approach to decouple anatomy and physiology from measurements of a cornea, allowing for characterization of pathologies through corneal thickness measurements. Another significant contribution resulting from the corneal model allows five of the corneal layer boundaries to be automatically located and has already been used to process thousands of UHROCT tomograms. Recent studies using this method have also been used to correlate contact-lens wear to hypoxia and corneal layer swelling. While corneal reconstruction represents the main application of this work, the reconstruction methodology can be extended to other medical imaging domains and can even represent temporal changes in tissue with minor modifications to the framework
Online learning of physics during a pandemic: A report from an academic experience in Italy
The arrival of the Sars-Cov II has opened a new window on teaching physics in academia.
Frontal lectures have left space for online teaching, teachers have been faced with a new way
of spreading knowledge, adapting contents and modalities of their courses. Students have
faced up with a new way of learning physics, which relies on free access to materials and
their informatics knowledge. We decided to investigate how online didactics has influenced
students’ assessments, motivation, and satisfaction in learning physics during the pandemic
in 2020. The research has involved bachelor (n = 53) and master (n = 27) students of
the Physics Department at the University of Cagliari (N = 80, 47 male; 33 female). The
MANOVA supported significant mean differences about gender and university level with
higher values for girls and master students in almost all variables investigated. The path
analysis showed that student-student, student-teacher interaction, and the organization of
the courses significantly influenced satisfaction and motivation in learning physics. The
results of this study can be used to improve the standards of teaching in physics at the
University of Cagliar
Social work with airports passengers
Social work at the airport is in to offer to passengers social services. The main
methodological position is that people are under stress, which characterized by a
particular set of characteristics in appearance and behavior. In such circumstances
passenger attracts in his actions some attention. Only person whom he trusts can help him
with the documents or psychologically