Robustness evaluation of a computer-aided detection system for pulmonary embolism (PE) in CTPA using independent test set from multiple institutions

2015 ◽  
Author(s):  
Chuan Zhou ◽  
Heang-Ping Chan ◽  
Aamer Chughtai ◽  
Jean W. Kuriakose ◽  
Ella A. Kazerooni ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Detection System ◽  
Computer Aided Detection ◽  
Test Set ◽  
Computer Aided ◽  
Independent Test

Accuracy of Segmentation of a Commercial Computer-aided Detection System for Mammography

Radiology ◽  
2005 ◽  
Vol 235 (2) ◽  
pp. 385-390 ◽  
Author(s):  
Jay A. Baker ◽  
Eric L. Rosen ◽  
Michele M. Crockett ◽  
Joseph Y. Lo
Keyword(s):  
Detection System ◽  
Computer Aided Detection ◽  
Computer Aided

scholarly journals Computer-Aided System Application Value for Assessing Hip Development

2020 ◽  
Vol 11 ◽  
Author(s):  
Yaoxian Jiang ◽  
Guangyao Yang ◽  
Yuan Liang ◽  
Qin Shi ◽  
Boqi Cui ◽  
...  
Keyword(s):  
Hip Joint ◽  
Detection System ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Diagnostic Efficiency ◽  
X Rays ◽  
Computer Aided Detection ◽  
Sharp Angle ◽  
Center Edge ◽  
Computer Aided

PurposeA computer-aided system was used to semiautomatically measure Tönnis angle, Sharp angle, and center-edge (CE) angle using contours of the hip bones to establish an auxiliary measurement model for developmental screening or diagnosis of hip joint disorders.MethodsWe retrospectively analyzed bilateral hip x-rays for 124 patients (41 men and 83 women aged 20–70 years) who presented at the Affiliated Zhongshan Hospital of Dalian University in 2017 and 2018. All images were imported into a computer-aided detection system. After manually outlining hip bone contours, Tönnis angle, Sharp angle, and CE angle marker lines were automatically extracted, and the angles were measured and recorded. An imaging physician also manually measured all angles and recorded hip development, and Pearson correlation coefficients were used to compare computer-aided system measurements with imaging physician measurements. Accuracy for different angles was calculated, and the area under the receiver operating characteristic (AUROC) curve was used to represent the diagnostic efficiency of the computer-aided system.ResultsFor Tönnis angle, Sharp angle, and CE angle, correlation coefficients were 0.902, 0.887, and 0.902, respectively; the accuracies of the computer-aided detection system were 89.1, 93.1, and 82.3%; and the AUROC curve values were 0.940, 0.956, and 0.948.ConclusionThe measurements of Tönnis angle, Sharp angle, and CE angle using the semiautomatic system were highly correlated with the measurements of the imaging physician and can be used to assess hip joint development with high accuracy and diagnostic efficiency.

Application of deep learning–based computer-aided detection system: detecting pneumothorax on chest radiograph after biopsy

2019 ◽  
Vol 29 (10) ◽  
pp. 5341-5348 ◽  
Author(s):  
Sohee Park ◽  
Sang Min Lee ◽  
Namkug Kim ◽  
Jooae Choe ◽  
Yongwon Cho ◽  
...  
Keyword(s):  
Deep Learning ◽  
Chest Radiograph ◽  
Detection System ◽  
Computer Aided Detection ◽  
Computer Aided
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