scholarly journals Cardiac motion estimation using multi-scale feature points

2008 ◽  
Author(s):  
Alessandro Becciu ◽  
Hans C. van Assen ◽  
Luc Florack ◽  
Bart J. Janssen ◽  
Bart Ter haar romeny
Keyword(s):  
Magnetic Resonance ◽  
Optic Flow ◽  
Causes Of Death ◽  
Cardiac Motion ◽  
Feature Points ◽  
Aperture Problem ◽  
Multi Scale ◽  
Harmonic Phase ◽  
The World ◽  
Suitable Framework

Heart illnesses influence the functioning of the cardiac muscle and are the major causes of death in the world. Optic flow methods are essential tools to assess and quantify the contraction of the cardiac walls, but are hampered by the aperture problem. Harmonic phase (HARP) techniques measure the phase in magnetic resonance (MR) tagged images. Due to the regular geometry, patterns generated by a combination of HARPs and sine HARPs represent a suitable framework to extract landmark features. In this paper we introduce a new aperture-problem free method to study the cardiac motion by tracking multi-scale features such as maxima, minima, saddles and corners, on HARP and sine HARP tagged images.

A Multi-scale Feature Based Optic Flow Method for 3D Cardiac Motion Estimation

2009 ◽  
pp. 588-599 ◽  
Author(s):  
Alessandro Becciu ◽  
Hans van Assen ◽  
Luc Florack ◽  
Sebastian Kozerke ◽  
Vivian Roode ◽  
...  
Keyword(s):  
Motion Estimation ◽  
Optic Flow ◽  
Cardiac Motion ◽  
Scale Feature ◽  
Flow Method ◽  
Multi Scale ◽  
Feature Based

scholarly journals Mortality beyond emergency threshold in a silent crisis– results from a population-based mortality survey in Ouaka prefecture, Central African Republic, 2020

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Eve Robinson ◽  
Lawrence Lee ◽  
Leslie F. Roberts ◽  
Aurelie Poelhekke ◽  
Xavier Charles ◽  
...  
Keyword(s):  
Central African Republic ◽  
Causes Of Death ◽  
Maternal Mortality Ratio ◽  
Mortality Rates ◽  
Population Based ◽  
Access To Healthcare ◽  
Mortality Data ◽  
Humanitarian Emergency ◽  
The World ◽  
Mortality Survey

Abstract Background The Central African Republic (CAR) suffers a protracted conflict and has the second lowest human development index in the world. Available mortality estimates vary and differ in methodology. We undertook a retrospective mortality study in the Ouaka prefecture to obtain reliable mortality data. Methods We conducted a population-based two-stage cluster survey from 9 March to 9 April, 2020 in Ouaka prefecture. We aimed to include 64 clusters of 12 households for a required sample size of 3636 persons. We assigned clusters to communes proportional to population size and then used systematic random sampling to identify cluster starting points from a dataset of buildings in each commune. In addition to the mortality survey questions, we included an open question on challenges faced by the household. Results We completed 50 clusters with 591 participating households including 4000 household members on the interview day. The median household size was 7 (interquartile range (IQR): 4—9). The median age was 12 (IQR: 5—27). The birth rate was 59.0/1000 population (95% confidence interval (95%-CI): 51.7—67.4). The crude and under-five mortality rates (CMR & U5MR) were 1.33 (95%-CI: 1.09—1.61) and 1.87 (95%-CI: 1.37–2.54) deaths/10,000 persons/day, respectively. The most common specified causes of death were malaria/fever (16.0%; 95%-CI: 11.0–22.7), violence (13.2%; 95%-CI: 6.3–25.5), diarrhoea/vomiting (10.6%; 95%-CI: 6.2–17.5), and respiratory infections (8.4%; 95%-CI: 4.6–14.8). The maternal mortality ratio (MMR) was 2525/100,000 live births (95%-CI: 825—5794). Challenges reported by households included health problems and access to healthcare, high number of deaths, lack of potable water, insufficient means of subsistence, food insecurity and violence. Conclusions The CMR, U5MR and MMR exceed previous estimates, and the CMR exceeds the humanitarian emergency threshold. Violence is a major threat to life, and to physical and mental wellbeing. Other causes of death speak to poor living conditions and poor access to healthcare and preventive measures, corroborated by the challenges reported by households. Many areas of CAR face similar challenges to Ouaka. If these results were generalisable across CAR, the country would suffer one of the highest mortality rates in the world, a reminder that the longstanding “silent crisis” continues.

scholarly journals TREASURE: Text Mining Algorithm Based On Affinity Analysis and Set Intersection to Find the Action of Tuberculosis Drugs against Other Pathogens

2021 ◽  
Vol 11 (15) ◽  
pp. 6834
Author(s):  
Pradeepa Sampath ◽  
Nithya Shree Sridhar ◽  
Vimal Shanmuganathan ◽  
Yangsun Lee
Keyword(s):  
Text Mining ◽  
Causes Of Death ◽  
Intersection Property ◽  
Research Papers ◽  
Bacterial Diseases ◽  
Mining Algorithm ◽  
Set Intersection ◽  
The World ◽  
Medical Researchers

Tuberculosis (TB) is one of the top causes of death in the world. Though TB is known as the world’s most infectious killer, it can be treated with a combination of TB drugs. Some of these drugs can be active against other infective agents, in addition to TB. We propose a framework called TREASURE (Text mining algoRithm basEd on Affinity analysis and Set intersection to find the action of tUberculosis dRugs against other pathogEns), which particularly focuses on the extraction of various drug–pathogen relationships in eight different TB drugs, namely pyrazinamide, moxifloxacin, ethambutol, isoniazid, rifampicin, linezolid, streptomycin and amikacin. More than 1500 research papers from PubMed are collected for each drug. The data collected for this purpose are first preprocessed, and various relation records are generated for each drug using affinity analysis. These records are then filtered based on the maximum co-occurrence value and set intersection property to obtain the required inferences. The inferences produced by this framework can help the medical researchers in finding cures for other bacterial diseases. Additionally, the analysis presented in this model can be utilized by the medical experts in their disease and drug experiments.

scholarly journals A deep-learning-based prognostic nomogram integrating microscopic digital pathology and macroscopic magnetic resonance images in nasopharyngeal carcinoma: a multi-cohort study

2020 ◽  
Vol 12 ◽  
pp. 175883592097141
Author(s):  
Fan Zhang ◽  
Lian-Zhen Zhong ◽  
Xun Zhao ◽  
Di Dong ◽  
Ji-Jin Yao ◽  
...  
Keyword(s):  
Deep Learning ◽  
Magnetic Resonance ◽  
Nasopharyngeal Carcinoma ◽  
Treatment Failure ◽  
Digital Pathology ◽  
Imaging Features ◽  
Multi Scale ◽  
External Test ◽  
Whole Slide Images ◽  
Independent Cohort

Background: To explore the prognostic value of radiomics-based and digital pathology-based imaging biomarkers from macroscopic magnetic resonance imaging (MRI) and microscopic whole-slide images for patients with nasopharyngeal carcinoma (NPC). Methods: We recruited 220 NPC patients and divided them into training ( n = 132), internal test ( n = 44), and external test ( n = 44) cohorts. The primary endpoint was failure-free survival (FFS). Radiomic features were extracted from pretreatment MRI and selected and integrated into a radiomic signature. The histopathological signature was extracted from whole-slide images of biopsy specimens using an end-to-end deep-learning method. Incorporating two signatures and independent clinical factors, a multi-scale nomogram was constructed. We also tested the correlation between the key imaging features and genetic alternations in an independent cohort of 16 patients (biological test cohort). Results: Both radiomic and histopathologic signatures presented significant associations with treatment failure in the three cohorts (C-index: 0.689–0.779, all p < 0.050). The multi-scale nomogram showed a consistent significant improvement for predicting treatment failure compared with the clinical model in the training (C-index: 0.817 versus 0.730, p < 0.050), internal test (C-index: 0.828 versus 0.602, p < 0.050) and external test (C-index: 0.834 versus 0.679, p < 0.050) cohorts. Furthermore, patients were stratified successfully into two groups with distinguishable prognosis (log-rank p < 0.0010) using our nomogram. We also found that two texture features were related to the genetic alternations of chromatin remodeling pathways in another independent cohort. Conclusion: The multi-scale imaging features showed a complementary value in prognostic prediction and may improve individualized treatment in NPC.

scholarly journals Empowering Urban Governance through Urban Science: Multi-Scale Dynamics of Urban Systems Worldwide

2020 ◽  
Vol 12 (15) ◽  
pp. 5954
Author(s):  
Juste Raimbault ◽  
Eric Denis ◽  
Denise Pumain
Keyword(s):  
Urban Growth ◽  
Path Dependence ◽  
Dynamic Models ◽  
Network Flows ◽  
City Size ◽  
Urban Systems ◽  
Scale Model ◽  
Multi Scale ◽  
The World ◽  
Urban Science

Cities are facing many sustainability issues in the context of the current global interdependency characterized by an economic uncertainty coupled to climate changes, which challenge their local policies aiming to better conciliate reasonable growth with livable urban environment. The urban dynamic models developed by the so-called “urban science” can provide a useful foundation for more sustainable urban policies. It implies that their proposals have been validated by correct observations of the diversity of situations in the world. However, international comparisons of the evolution of cities often produce unclear results because national territorial frameworks are not always in strict correspondence with the dynamics of urban systems. We propose to provide various compositions of systems of cities in order to better take into account the dynamic networking of cities that go beyond regional and national territorial boundaries. Different models conceived for explaining city size and urban growth distributions enable the establishing of a correspondence between urban trajectories when observed at the level of cities and systems of cities. We test the validity and representativeness of several dynamic models of complex urban systems and their variations across regions of the world, at the macroscopic scale of systems of cities. The originality of the approach resides in the way it considers spatial interaction and evolutionary path dependence as major features in the general behavior of urban entities. The models studied include diverse and complementary processes, such as economic exchanges, diffusion of innovations, and physical network flows. Complex systems dynamics is in principle unpredictable, but contextualizing it regarding demographic, income, and resource components may help in minimizing the forecasting errors. We use, among others, a new unique source correlating population and built-up footprint at world scale: the Global Human Settlement built-up areas (GHS-BU). Following the methodology and results already obtained in the European GeoDiverCity project, including USA, Europe, and BRICS countries, we complete them with this new dataset at world scale and different models. This research helps in further empirical testing of the hypotheses of the evolutionary theory of urban systems and partially revising them. We also suggest research directions towards the coupling of these models into a multi-scale model of urban growth.

Vision for mobile robots

1992 ◽  
Vol 337 (1281) ◽  
pp. 341-350 ◽  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Structure From Motion ◽  
Optic Flow ◽  
Image Sequences ◽  
Additional Constraint ◽  
Feature Points ◽  
Scene Structure ◽  
Corner Points ◽  
Edge Points

Localized feature points, particularly corners, can be computed rapidly and reliably in images, and they are stable over image sequences. Corner points provide more constraint than edge points, and this additional constraint can be propagated effectively from corners along edges. Implemented algorithms are described to compute optic flow and to determine scene structure for a mobile robot using stereo or structure from motion. It is argued that a mobile robot may not need to compute depth explicitly in order to navigate effectively.

scholarly journals Carbon Dots for Cancer Nanomedicine: A Bright Future

2021 ◽  
Author(s):  
Samer Bayda ◽  
Emanuele Amadio ◽  
Simone Cailotto ◽  
Yahima Frión-Herrera ◽  
Alvise Perosa ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Carbon Dots ◽  
Causes Of Death ◽  
Cancer Therapies ◽  
Therapeutic Approaches ◽  
Bright Future ◽  
Cancer Nanomedicine ◽  
The World

Cancer remains one of the main causes of death in the world. Early diagnosis and effective cancer therapies are required to treat this pathology. Traditional therapeutic approaches are limited by...

scholarly journals A New Rotor Position Measurement Method for Permanent Magnet Spherical Motors

2018 ◽  
Vol 8 (12) ◽  
pp. 2415 ◽  
Author(s):  
Yin Lu ◽  
Cungang Hu ◽  
Qunjing Wang ◽  
Yi Hong ◽  
Weixiang Shen ◽  
...  
Keyword(s):  
Permanent Magnet ◽  
High Speed ◽  
Measurement Method ◽  
Coordinate Frame ◽  
Feature Points ◽  
Position Measurement ◽  
Experimental Platform ◽  
Rotor Position ◽  
Straight Line ◽  
The World

This paper proposes a new high-precision rotor position measurement (RPM) method for permanent magnet spherical motors (PMSMs). In the proposed method, a LED light spot generation module (LSGM) was installed at the top of the rotor shaft. In the LSGM, three LEDs were arranged in a straight line with different distances between them, which were formed as three optical feature points (OFPs). The images of the three OFPs acquired by a high-speed camera were used to calculate the rotor position of PMSMs in the world coordinate frame. An experimental platform was built to verify the effectiveness of the proposed RPM method.

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