Left ventricle surface reconstruction from volumetric CT images by the fusion of clustering and active contours

1998 ◽  
Author(s):  
Li Fan ◽  
Chang W. Chen
Keyword(s):  
Left Ventricle ◽  
Surface Reconstruction ◽  
Active Contours ◽  
Ct Images ◽  
Volumetric Ct

Active contours driven by localizing region and edge-based intensity fitting energy with application to segmentation of the left ventricle in cardiac CT images

2015 ◽  
Vol 156 ◽  
pp. 199-210 ◽  
Author(s):  
Yan Zhou ◽  
Wei-Ren Shi ◽  
Wei Chen ◽  
Yong-lin Chen ◽  
Ying Li ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Cardiac Ct ◽  
Active Contours ◽  
Ct Images ◽  
Edge Based

scholarly journals Deep Learning Method for Quantitative Analysis of Covid -19 using CT Chest Images

2021 ◽  
Author(s):  
Indrajeet Kumar ◽  
Jyoti Rawat
Keyword(s):  
Deep Learning ◽  
Diagnostic Tests ◽  
Ct Images ◽  
Rapid Diagnosis ◽  
Chest Ct ◽  
Visual Features ◽  
Learning Module ◽  
Volumetric Ct ◽  
The Cost

Abstract The manual diagnostic tests performed in laboratories for pandemic disease such as COVID19 is time-consuming, requires skills and expertise of the performer to yield accurate results. Moreover, it is very cost ineffective as the cost of test kits is high and also requires well-equipped labs to conduct them. Thus, other means of diagnosing the patients with presence of SARS-COV2 (the virus responsible for COVID19) must be explored. A radiography method like chest CT images is one such means that can be utilized for diagnosis of COVID19. The radio-graphical changes observed in CT images of COVID19 patient helps in developing a deep learning-based method for extraction of graphical features which are then used for automated diagnosis of the disease ahead of laboratory-based testing. The proposed work suggests an Artificial Intelligence (AI) based technique for rapid diagnosis of COVID19 from given volumetric CT images of patient’s chest by extracting its visual features and then using these features in the deep learning module. The proposed convolutional neural network is deployed for classifying the infectious and non-infectious SARS-COV2 subjects. The proposed network utilizes 746 chests scanned CT images of which 349 images belong to COVID19 positive cases while remaining 397 belong negative cases of COVID19. The extensive experiment has been completed with the accuracy of 98.4 %, sensitivity of 98.5 %, the specificity of 98.3 %, the precision of 97.1 %, F1score of 97.8 %. The obtained result shows the outstanding performance for classification of infectious and non-infectious for COVID19 cases.

scholarly journals MA-Shape: Modality Adaptation Shape Regression for Left Ventricle Segmentation on Mixed MR and CT Images

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 16584-16593 ◽  
Author(s):  
Jinyu Cong ◽  
Yuanjie Zheng ◽  
Wufeng Xue ◽  
Bofeng Cao ◽  
Shuo Li
Keyword(s):  
Left Ventricle ◽  
Ct Images ◽  
Shape Regression ◽  
Ventricle Segmentation

Can computed tomodensitometry predict ventricular pseudoaneurysm occurrence after heart valve endocarditis?

2019 ◽  
Vol 29 (09) ◽  
pp. 1206-1207
Author(s):  
Virginie Fouilloux ◽  
Philippe Aldebert ◽  
Guillaume Gorincour
Keyword(s):  
Left Ventricle ◽  
Ct Scan ◽  
Heart Valve ◽  
Lateral Wall ◽  
Ct Images

AbstractVentricular pseudoaneurysm is a rare but well-known complication after valvular endocarditis. The lesion was localised exactly where pre-operative CT scan showed lack of enhancement in the postero-lateral wall of the left ventricle. This case demonstrates how much attention must be paid to myocardial CT images and emphazises the need of close follow-up in patients with infective endocartitis.

An aneurysmal right coronary artery fistula draining into the left ventricle

2017 ◽  
Vol 27 (6) ◽  
pp. 1214-1215
Author(s):  
Dongxu Li ◽  
Yabo Wang ◽  
Qi An
Keyword(s):  
Coronary Artery ◽  
Left Ventricle ◽  
Right Coronary Artery ◽  
Rare Case ◽  
Median Sternotomy ◽  
Coronary Artery Fistula ◽  
Ct Images ◽  
Coronary Ct

AbstractWe describe a rare case of aneurysmal right coronary artery drainage into left ventricle in a 38-year old male with entailed coronary CT images. After median sternotomy surgery, the patient recovered well.

Segmentation of the Left Ventricle from Cardiac MR Images Using Active Contours with NEGVF

2012 ◽  
Vol 1 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Lixiong Liu ◽  
Jiakun Song ◽  
Mengjuan Chen ◽  
Bao Liu
Keyword(s):  
Left Ventricle ◽  
Active Contours ◽  
Mr Images ◽  
Cardiac Mr
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