scholarly journals A Software Tool for Heart AVJ Motion Tracking Using Cine Cardiovascular Magnetic Resonance Images

Author(s):  
Pengdong Xiao ◽  
Xiaodan Zhao ◽  
Shuang Leng ◽  
Ru San Tan ◽  
Philip Wong ◽  
...  
Diagnostics ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 47 ◽  
Author(s):  
Carlos López-Gómez ◽  
Rafael Ortiz-Ramón ◽  
Enrique Mollá-Olmos ◽  
David Moratal ◽  

The current criteria for diagnosing Alzheimer’s disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has become one of the main research focuses. The purpose of the present study was to evaluate a set of texture parameters as potential biomarkers of the disease. To this end, the ALTEA (ALzheimer TExture Analyzer) software tool was created to perform 2D and 3D texture analysis on magnetic resonance images. This intuitive tool was used to analyze textures of circular and spherical regions situated in the right and left hippocampi of a cohort of 105 patients: 35 AD patients, 35 patients with early mild cognitive impairment (EMCI) and 35 cognitively normal (CN) subjects. A total of 25 statistical texture parameters derived from the histogram, the Gray-Level Co-occurrence Matrix and the Gray-Level Run-Length Matrix, were extracted from each region and analyzed statistically to study their predictive capacity. Several textural parameters were statistically significant (p < 0.05) when differentiating AD subjects from CN and EMCI patients, which indicates that texture analysis could help to identify the presence of AD.


2021 ◽  
Vol 10 (3) ◽  
pp. 503
Author(s):  
Gregorio Bernabé ◽  
José D. Casanova ◽  
Josefa González-Carrillo ◽  
Juan R. Gimeno-Blanes

Left ventricular non-compaction (LVNC) is defined by an increase of trabeculations in left ventricular (LV) endomyocardium. Although LVNC can be in isolation, an increase in hypertrabeculation often accompanies genetic cardiomyopathies. Current methods for quantification of LV trabeculae have limitations. Several improvements are proposed and implemented to enhance a software tool to quantify the trabeculae degree in the LV myocardium in an accurate and automatic way for a population of patients with genetic cardiomyopathies (QLVTHCI). The software tool is developed and evaluated for a population of 59 patients (470 end-diastole cardiac magnetic resonance images). This tool produces volumes of the compact sector and the trabecular area, the proportion between these volumes, and the left ventricular and trabeculated masses. Substantial enhancements are obtained over the manual process performed by cardiologists, so saving important diagnosis time. The parallelization of the detection of the external layer is proposed to ensure real-time processing of a patient, obtaining speed-ups from 7.5 to 1500 with regard to QLVTHCI and the manual process used traditionally by cardiologists. Comparing the method proposed with the fractal proposal to differentiate LVNC and non-LVNC patients among 27 subjects with previously diagnosed cardiomyopathies, QLVTHCI presents a full diagnostic accuracy, while the fractal criteria achieve 78%. Moreover, QLTVHCI can be installed and integrated in hospitals on request, whereas the high cost of the license of the fractal method per year of this tool has prevented reproducibility by other medical centers.


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