  This study was conducted to develop a computer-aided detection (CAD) system
for triaging patients with pulmonary embolism (PE). The purpose of the system
was to reduce the death rate during the waiting period. Computed tomography
pulmonary angiography (CTPA) is used for PE diagnosis. Because CTPA reports
require a radiologist to review the case and suggest further management, this
creates a waiting period during which patients may die. Our proposed CAD method
was thus designed to triage patients with PE from those without PE. In contrast
to related studies involving CAD systems that identify key PE lesion images to
expedite PE diagnosis, our system comprises a novel classification-model
ensemble for PE detection and a segmentation model for PE lesion labeling. The
models were trained using data from National Cheng Kung University Hospital and
open resources. The classification model yielded 0.73 for receiver operating
characteristic curve (accuracy = 0.85), while the mean intersection over union
was 0.689 for the segmentation model. The proposed CAD system can distinguish
between patients with and without PE and automatically label PE lesions to
expedite PE diagnosis
