- Validation of a New Image-Based Approach for the Accurate Estimating of the Growth Rate of Detected Lung Nodules Using Real Computed Tomography Images and Elastic Phantoms Generated by State-of-the-Art Microfluidics Technology

2016 ◽  
pp. 418-433
Keyword(s):  
Computed Tomography ◽  
Growth Rate ◽  
State Of The Art ◽  
Lung Nodules ◽  
Computed Tomography Images

scholarly journals Factors influencing infarct growth including collateral status assessed using computed tomography in acute stroke patients with large artery occlusion

2019 ◽  
Vol 14 (6) ◽  
pp. 603-612 ◽  
Author(s):  
Bin Jiang ◽  
Robyn L Ball ◽  
Patrik Michel ◽  
Ying Li ◽  
Guangming Zhu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Growth Rate ◽  
Growth Rates ◽  
Artery Occlusion ◽  
Conditional Inference ◽  
Imaging Biomarkers ◽  
Large Artery ◽  
Perfusion Computed Tomography ◽  
Computed Tomography Images ◽  
Head Computed Tomography

In major ischemic stroke caused by a large artery occlusion, neuronal loss varies considerably across individuals without revascularization. This study aims to identify which patient characteristics are most highly associated with this variability. Demographic and clinical information were retrospectively collected on a registry of 878 patients. Imaging biomarkers including Alberta Stroke Program Early CT score, noncontrast head computed tomography infarct volume, perfusion computed tomography infarct core and penumbra, occlusion site, collateral score, and recanalization status were evaluated on the baseline and early follow-up computed tomography images. Infarct growth rates were calculated by dividing infarct volumes by the time elapsed between the computed tomography scan and the symptom onset. Collateral score was graded into four levels (0, 1, 2, and 3) in comparison with the normal side. Correlation of perfusion computed tomography and noncontrast head computed tomography infarct volumes and infarct growth rates were estimated with the nonparametric Spearman's rank correlation. Conditional inference trees were used to identify the clinical and imaging biomarkers that were most highly associated with the infarct growth rate and modified Rankin Scale at 90 days. Two hundred and thirty-two patients met the inclusion criteria for this study. The median infarct growth rates for perfusion computed tomography and noncontrast head computed tomography were 11.2 and 6.2 ml/log(min) in logarithmic model, and 18.9 and 10.4 ml/h in linear model, respectively. Noncontrast head computed tomography and perfusion computed tomography infarct volumes and infarct growth rates were significantly correlated (rho=0.53; P < 0.001). Collateral status was the strongest predictor for infarct growth rates. For collateral=0, the perfusion computed tomography and noncontrast head computed tomography infarct growth rate were 31.56 and 16.86 ml/log(min), respectively. Patients who had collateral >0 and penumbra volumes>92 ml had the lowest predicted perfusion computed tomography infarct growth rates (6.61 ml/log(min)). Collateral status was closely related to the diversity of infarct growth rates, poor collaterals were associated with a faster infarct growth rates and vice versa.

scholarly journals Development of Computer-aided Diagnostic System for Detection of Lung Nodules in Three-dimensional Computed Tomography Images

2006 ◽  
Vol 62 (4) ◽  
pp. 555-564 ◽  
Author(s):  
Megumi Yamamoto ◽  
Takayuki Ishida ◽  
Ikuo Kawashita ◽  
Masayuki Kagemoto ◽  
Koichi Fujikawa ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
Diagnostic System ◽  
Lung Nodules ◽  
Computed Tomography Images ◽  
Computer Aided

Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening1

2004 ◽  
Vol 11 (6) ◽  
pp. 617-629 ◽  
Author(s):  
Hidetaka Arimura ◽  
Shigehiko Katsuragawa ◽  
Kenji Suzuki ◽  
Feng Li ◽  
Junji Shiraishi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Low Dose ◽  
Automated Detection ◽  
Lung Nodules ◽  
Computed Tomography Images ◽  
Low Dose Computed Tomography

Segmentation of Lung Nodules in Computed Tomography Images Using Dynamic Programming and Multidirection Fusion Techniques1

2009 ◽  
Vol 16 (6) ◽  
pp. 678-688 ◽  
Author(s):  
Qian Wang ◽  
Enmin Song ◽  
Renchao Jin ◽  
Ping Han ◽  
Xiaotong Wang ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Dynamic Programming ◽  
Lung Nodules ◽  
Computed Tomography Images
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