Diana Giraldo- PhD
- PostDoc Position at University of Antwerp
Diana Giraldo
- PhD
- PostDoc Position at University of Antwerp
About
27
Publications
1,365
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
90
Citations
Introduction
Diana Giraldo currently works at National University of Colombia. Diana does research in Biomedical Engineering and Computing in Mathematics, Natural Science, Engineering and Medicine.
Current institution
Publications
Publications (27)
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system that results in varying degrees of functional impairment. Conventional tools, such as the Expanded Disability Status Scale (EDSS), lack sensitivity to subtle changes in disease progression. Radiomics offers a quantitative imaging approach to address this limitatio...
Introduction
Magnetic resonance imaging (MRI) is crucial for diagnosing and monitoring of multiple sclerosis (MS) as it is used to assess lesions in the brain and spinal cord. However, in real-world clinical settings, MRI scans are often acquired with thick slices, limiting their utility for automated quantitative analyses. This work presents a sin...
Magnetic resonance imaging (MRI) is crucial for diagnosing and monitoring of multiple sclerosis (MS) as it is used to assess lesions in the brain and spinal cord. However, in real-world clinical settings, MRI scans are often acquired with thick slices, limiting their utility for automated quantitative analyses. This work presents a single-image sup...
Due to acquisition time constraints, T2-w FLAIR MRI of Multiple Sclerosis (MS) patients is often acquired with multi-slice 2D protocols with a low through-plane resolution rather than with high-resolution 3D protocols. Automated lesion segmentation on such low-resolution (LR) images, however, performs poorly and leads to inaccurate lesion volume es...
In this work, we compare the results of analyzing group differences in Alzheimer’s Disease (AD) with two different models for multi-shell diffusion MRI: the Diffusion Kurtosis Tensor (DKT) and Multi-Tissue Constrained Spherical Deconvolution (MT-CSD). Separate analysis for DKT metrics and measures derived from MT-CSD were performed to investigate d...
Background
Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer’s disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume ef...
Introduction:
Neuropsychological test scores are limited and standard outcomes may mask the heterogeneity of cognitive impairment. This article presents the calculation and evaluation of six composite scores that quantify domain-specific impairment.
Methods:
Parameters for composite scores calculation were learned by performing confirmatory fact...
Background. Traumatic brain injury (TBI) is associated with altered white matter organization and impaired cognitive functioning. Objective. We aimed to investigate changes in white matter and cognitive functioning following computerized cognitive training. Methods. Sixteen adolescents with moderate-to-severe TBI (age 15.6 ± 1.8 years, 1.2-4.6 year...
Purpose
This work presents an automatic characterization of the Alzheimer's disease describing the illness as a multidirectional departure from a baseline defining the control state, being these directions determined by a distance between functional‐equivalent anatomical regions.
Methods
After a brain parcellation, a region is described by its his...
Structural Magnetic Resonance (MR) brain images should provide quantitative information about the stage and progression of Alzheimer’s disease. However, the use of MRI is limited and practically reduced to corroborate a diagnosis already performed with neuropsychological tools. This paper presents an automated strategy for extraction of relevant an...
Objetivo
Proponer y evaluar un modelo para el ajuste y predicción de la mortalidad en Colombia que permita analizar tendencias por edad, sexo, Departamento y causa.
Metodología
Los registros de defunciones no fetales fueron utilizados como fuente primaria de análisis. Estos datos se pre-procesaron recodificando las causas y redistribuyendo los cód...
ABSTRACT Objective To propose and evaluate a model for fitting and forecasting the mortality rates in Colombia that allows analyzing the trends by age, sex, region and cause of death. Methodology The national death registries were used as primary source of analysis. The data was pre-processed recodifying the cause of death and redistributing the ga...
Initial diagnosis of Alzheimer's disease (AD) is based on the patient's clinical history and a battery of neuropsy-chological tests. This work presents an automatic strategy that uses Structural Magnetic Resonance Imaging (MRI) to learn brain models for different stages of the disease using information from clinical assessments. Then, a comparison...
An accurate ventricular function quantification is important to support evaluation, diagnosis and prognosis of several cardiac pathologies. However, expert heart delineation, specifically for the right ventricle, is a time consuming task with high inter-and-intra observer variability. A fully automatic 3D+time heart segmentation framework is herein...
Alzheimer's disease (AD) is a neurodegenerative disease that affects higher brain functions. Initial diagnosis of AD is based on the patient's clinical history and a battery of neuropsychological tests. The accuracy of the diagnosis is highly dependent on the examiner's skills and on the evolution of a variable clinical frame. This work presents an...
Morphometry based methods allow the detection of subtle anatomical differences in the Magnetic Resonance Images (MRI) between healthy subjects and Alzheimer's Disease (AD) patients. However, anatomical volumes are rarely used for clinical diagnosis as the changes induced by AD are hard to differentiate from normal brain aging.
We present a morphome...
This paper presents a fully automatic method that condenses relevant morphometric information from a database of magnetic resonance images (MR) labeled as either normal (NC) or Alzheimer's disease (AD). The proposed method generates class templates using Nonnegative Matrix Factorization (NMF) which will be used to develop an NC/AD classi cator. It...
