Public Articles
Circuito RC
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Master Thesis notes
Alzheimer's Disease
This is a working-paper/pre-print of the first chapter of my PhD thesis: https://tel.archives-ouvertes.fr/tel-01384678
Alois Alzheimer in 1907 reported a study of one of his patients with “an unusual illness of the cerebral cortex” \cite{Alzheimer1907,stelzmann1995}. Alzheimer details the symptoms of his patient suggesting that they were so unusual that the patient could not be classified as having one of the recognized illnesses.
“The first symptom the 51-year-old woman showed was the idea that she was jealous of her husband. Soon she developed a rapid loss of memory. She was disoriented in her home, carried things from one place to another and hid them, sometimes she thought somebody was trying to kill her and started to cry loudly. ... As the illness progressed, these phenomena which are to be interpreted as complex symptoms appear sometimes stronger, sometimes weaker. But they are never severe. On the other hand, the imbecility of the patient increased in general. Her death occurred after four and a half years of illness. At the end, the patient was lying in bed in a fetal position completely pathetic, incontinent. In spite of all nursing care, she had developed bedsores. ... The post-mortem showed an evenly atrophic brain without macroscopic focal degeneration. ... the nucleus and the cell itself disintegrate and only a tangle of fibrils indicates the place where a neuron was previously located. ... Many neurons, especially the ones in the upper layer, have completely disappeared. ... Distributed all over the cortex, but especially numerous in the upper layers, there are minute miliary foci which are caused by the deposition of a special substance in the cortex. ... Considering everything, it seems we are dealing here with a special illness.”
More than a century now, indeed Alzheimer was right that he was dealing with a special illness which is now named after himself, as Alzheimer’s Disease (AD). Ever since this first reporting, several studies have been performed in the past century and in particular the last couple of decades. However, the exact mechanisms of AD and its causes are poorly understood, and there is no cure till date.
A Biophysical Model of Brain Deformation to Simulate and Analyse Longitudinal MRIs of Patients with Alzheimer's Disease
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This is a pre-print (a working paper) of the following published paper:
Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, Xavier Pennec. A biophysical model of brain deformation to simulate and analyze longitudinal MRIs of patients with Alzheimer’s disease. NeuroImage, Elsevier, 2016, 134, pp.35-52.
We propose a framework for developing a comprehensive biophysical model that could predict and simulate realistic longitudinal MRIs of patients with Alzheimer’s Disease (AD). The framework includes three major building blocks: i) Atrophy generation ii) Brain deformation iii) Realistic MRI generation. Within this framework, this paper focuses on a detailed implementation of the brain deformation block with a carefully designed biomechanics-based tissue loss model. For a given baseline brain MRI, the model yields a deformation field imposing the desired atrophy at each voxel of the brain parenchyma while allowing the CSF to expand as required to globally compensate for the locally prescribed volume loss. Our approach is inspired by biomechanical principles and involves a system of equations similar to Stokes equations in fluid mechanics but with the presence of a non-zero mass source term. We use this model to simulate longitudinal MRIs by prescribing complex patterns of atrophy. We explore the influence of different spatial distributions of atrophy on the image appearance . The proposed framework could help understand the implications of different model assumptions, regularization choices and spatial priors for the detection and measurement of brain atrophy from longitudinal brain MRIs.
biophysical model, Alzheimer’s disease, simulation of atrophy, longitudinal MRIs simulation, longitudinal modeling
Simulating Patient Specific Multiple Time-point MRIs From a Biophysical Model of Brain Deformation in Alzheimer's Disease
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This paper proposes a framework to simulate patient specific structural Magnetic Resonance Images (MRIs) from the available time-points of Alzheimer’s Disease(AD) subjects. We use a biophysical model of brain deformation due to atrophy that can generate biologically plausible deformation for any given desired volume changes at the voxel level of the brain MRI. Large number of brain regions are segmented in 45 AD patients and the atrophy rates per year are estimated in these regions from two extremal available scans. Assuming linear progression of atrophy, the volume changes in scans closest to the middle time-point images from the baseline scans are computed. These atrophy maps are prescribed to the baseline images to simulate the middle time-point images by using the biophysical model of brain deformation. The volume changes from the baseline image to the real middle time-point are compared to the volume changes in the simulated middle time-point images. This present framework also allows to introduce desired atrophy patterns at different time-points to simulate non-linear progression of atrophy. This opens a way to use a biophysical model of brain deformation to evaluate methods that study the temporal progression and spatial relationships of atrophy evolution in AD.
Keywords: Alzheimer’s disease, biophysical modeling, biomechanical simulation
This is a pre-print of the following published article: Bishesh Khanal, Marco Lorenzi, Nicholas Ayache, Xavier Pennec. Simulating Patient Specific Multiple Time-point MRIs From a Biophysical Model of Brain Deformation in Alzheimer’s Disease. Workshop on Computational Biomechanics for Medicine - X, Oct 2015, Munich, France. 2015.
Course Outline for HLTH 462
Gravitational Waves: The First Swell!
A Big Discovery
On 14 September 2015 at 4:50:45 AM Eastern standard time, the LIGO experiment detected for the first time the passage of gravitational waves. Scientists saw a very specific pattern of stretching and compression of space-time called a “chirp”. The detection was done independently at the two locations of the experiment, one in Hanford (Washington) and the other one in Livingstone (Louisiana). This amazing discovery has occurred almost exactly 100 years after Albert Einstein published his General Theory of Relativy \citep{1916AnP...354..769E}, and represents the last verification of this beautiful theory of gravity.
How did the waves look like? Glassy and double-overhead!
Curating cosmic-ray datasets in a dedicated repository: motivations, challenges and advantages
Comparaison de modèles en cosmologie : bootstrap
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Circuito RLC
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Frontiers In Cellular Neuroscience Template
DM and osteoporosis
Aplicación de la estrella Boehm turner a los proyectos de desarrollo de software en la Universidad de Guayaquil
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Circuito RC
and 3 collaborators
Bayesian model comparison of alternative cosmologies
and 1 collaborator
In this work, we make a statistical comparison of some known cosmological models: The cosmological constant (ΛCDM) model, the constant equation-of-state (wCDM) model, the CPL dark energy parameterization, the Dvali-Gabadadze-Porrati (DGP) model, a vacuum-decay (Λ(t)CDM) model and also the power-law f(R) model in the metric formalism. For this purpose, we perform a Bayesian model selection analysis using the Affine-Invariant Ensemble Sampler Monte-Carlo method. In order to obtain the parametric space and the posterior distribution for the parameters of each model, we use the more up-to-date type Ia supernova (SNe Ia) data, the Joint Lightcurve Analysis (JLA) compilation, containing 740 events between 0.01 < z < 1.3. The model selection is then performed by obtaining the Bayesian evidence of each model and computing the Bayes factor between two models. The results indicate that the JLA data only cannot distinguish the standard ΛCDM from the Λ(t)CDM, power-law metric f(R) and DGP alternatives, but to make more strong conclusions, a more robust analysis including combining the SNe Ia data with other kind of observables is necessary.
All great truths begin as blasphemies: In Defense of "Silly" Research
The Sparse Analytic Hierarchy Process for large groups decision making
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Learning Authorea
The document record the basics HTML friendly LaTeX codes and shows some examples. It is for myself reference. I am learning authorea.
LaTeX is a programming language that can be used for writing documents. It is especially useful for the mathematics and sciences fields due to its ease of writing special symbols and equations while also making them look good. For those not using special characters LaTex requires minimal learning, making it a very approachable language. Most textbooks are actually written in LaTeX.
In this cheat sheet, we discuss some of the basics for writing documents in LaTeX. In particular, we will focus on web documents and introduce a subset of LaTeX which safely works on the web.
Structural Equation Modelling Tutorial
The proper care and feeding of your older graduate student.
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Ley de inducción de Faraday
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Is the Great Decoupling Real?
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