Detection and classification of lung abnormalities by use of convolutional neural network (CNN) and regions with CNN features (R-CNN)

Abstract

Image-based computer-aided diagnosis (CADx) algorithm by use of convolutional neural network (CNN) does not necessarily require an image-feature extractor. Therefore, image-based CADx is powerful compared with feature-based CADx that requires the image-feature extractor for differential diagnosis of lung abnormalities such as lung nodules and diffuse lung diseases. We have also developed an image-based computer-aided detection (CADe) algorithm by use of regions with CNN features (R-CNN) for detection of lung abnormalities. We evaluated the performance of image-based CADx by use of CNN and that of image-based CADe by use of R-CNN for various kinds of lung abnormalities such as lung nodules and diffuse lung diseases.

Ähnliche Arbeiten