title: Automated detection of endotracheal tubes in paediatric chest radiographs.
abstract: The aim of this study was to develop an automated method for the detection of endotracheal tube and location of its tip in paediatric chest radiographs. In this method, a seed point was first determined from the line crossing the cervical region and a line path was traced from the seed point. Two features, Lmax and C, were determined from the path and were combined to detect the existence of the endotracheal tube. Multiple thresholds applied to the line path were used to determine the candidate locations for the tip, and the most suitable location was selected from these candidates by analysing the image features. To evaluate the performance of detection of endotracheal tube existence, support vector machine was used to classify the images with and without endotracheal tubes on the basis of Lmax and C. The discriminant performance of the method was evaluated using receiver operating characteristic (ROC) analysis. To evaluate the precision of the detected tip locations, the tip locations in paediatric chest images were annotated by a radiologist. The distance (error) between the detected and annotated locations was used to evaluate detection precision for the tip location. The proposed method was evaluated using 528 images with endotracheal tubes and 816 images without endotracheal tubes. The discriminant performance in this study, evaluated as Az (area under the ROC curve), for detecting the existence of endotracheal tubes on the basis of the two features was 0.943±0.009, and the detection error of the tip location was 1.89±2.01mm. The proposed method obtained high performance results and could be useful for detecting the malposition of endotracheal tubes in paediatric chest radiographs.
authors.affiliation: Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan. Electronic address: tonykao@kmu.edu.tw.
authors.forename: E-Fong
authors.initials: EF
authors.lastname: Kao
authors.affiliation: Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
authors.forename: Twei-Shiun
authors.initials: TS
authors.lastname: Jaw
authors.affiliation: Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan.
authors.forename: Chun-Wei
authors.initials: CW
authors.lastname: Li
authors.affiliation: Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan.
authors.forename: Ming-Chung
authors.initials: MC
authors.lastname: Chou
authors.affiliation: Department of Medical Imaging, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
authors.forename: Gin-Chung
authors.initials: GC
authors.lastname: Liu
mesh_terms: D002648:Child; D006801:Humans; D007442:Intubation, Intratracheal / Q000009:adverse effects / Q000295:instrumentation*; D010363:Pattern Recognition, Automated / Q000379:methods; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic
keywords: Computer-aided detection; Endotracheal tube; Paediatric chest radiograph