Towards accurate segmentation of retinal vessels and the optic disc in fundoscopic images with generative adversarial networks
Automatic segmentation of the retinal vasculature and the optic disc is a crucial task for
accurate geometric analysis and reliable automated diagnosis. In recent years, Convolutional …
accurate geometric analysis and reliable automated diagnosis. In recent years, Convolutional …
[HTML][HTML] Development and validation of deep learning models for screening multiple abnormal findings in retinal fundus images
Purpose To develop and evaluate deep learning models that screen multiple abnormal
findings in retinal fundus images. Design Cross-sectional study. Participants For the …
findings in retinal fundus images. Design Cross-sectional study. Participants For the …
[HTML][HTML] DeNTNet: Deep Neural Transfer Network for the detection of periodontal bone loss using panoramic dental radiographs
In this study, a deep learning-based method for developing an automated diagnostic support
system that detects periodontal bone loss in the panoramic dental radiographs is proposed. …
system that detects periodontal bone loss in the panoramic dental radiographs is proposed. …
[HTML][HTML] Artificial intelligence in health care: Current applications and issues
In recent years, artificial intelligence (AI) technologies have greatly advanced and become a
reality in many areas of our daily lives. In the health care field, numerous efforts are being …
reality in many areas of our daily lives. In the health care field, numerous efforts are being …
Added value of deep learning–based detection system for multiple major findings on chest radiographs: a randomized crossover study
Background Previous studies assessing the effects of computer-aided detection on observer
performance in the reading of chest radiographs used a sequential reading design that may …
performance in the reading of chest radiographs used a sequential reading design that may …
Comparison of shallow and deep learning methods on classifying the regional pattern of diffuse lung disease
This study aimed to compare shallow and deep learning of classifying the patterns of
interstitial lung diseases (ILDs). Using high-resolution computed tomography images, two …
interstitial lung diseases (ILDs). Using high-resolution computed tomography images, two …
Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings
Objective To investigate the feasibility of a deep learning–based detection (DLD) system for
multiclass lesions on chest radiograph, in comparison with observers. Methods A total of …
multiclass lesions on chest radiograph, in comparison with observers. Methods A total of …
Psychoacoustic performance and music and speech perception in prelingually deafened children with cochlear implants
The number of pediatric cochlear implant (CI) recipients has increased substantially over the
past 10 years, and it has become more important to understand the underlying mechanisms …
past 10 years, and it has become more important to understand the underlying mechanisms …
[HTML][HTML] Development of a spine X-ray-based fracture prediction model using a deep learning algorithm
Background Since image-based fracture prediction models using deep learning are lacking,
we aimed to develop an X-ray-based fracture prediction model using deep learning with …
we aimed to develop an X-ray-based fracture prediction model using deep learning with …
[HTML][HTML] Deep learning algorithm for reducing CT slice thickness: effect on reproducibility of radiomic features in lung cancer
Objective To retrospectively assess the effect of CT slice thickness on the reproducibility of
radiomic features (RFs) of lung cancer, and to investigate whether convolutional neural …
radiomic features (RFs) of lung cancer, and to investigate whether convolutional neural …