1.9k citations · 2.4k across the 11 of their papers we have counts for
3 papers · 1 filter
Automatic classification of multiple catheters in neonatal radiographs with deep learning
Robert D. E. Henderson, Xin Yi, Scott J. Adams +1
We develop and evaluate a deep learning algorithm to classify multiple catheters on neonatal chest and abdominal radiographs. A convolutional neural network (CNN) was trained using…
AFD-Net: Adaptive Fully-Dual Network for Few-Shot Object Detection
Longyao Liu, Bo Ma, Yulin Zhang +2
Few-shot object detection (FSOD) aims at learning a detector that can fast adapt to previously unseen objects with scarce annotated examples, which is challenging and demanding. Ex…
Computer-Aided Assessment of Catheters and Tubes on Radiographs: How Good is Artificial Intelligence for Assessment?
Xin Yi, Scott J. Adams, Robert D. E. Henderson +1
Catheters are the second most common abnormal finding on radiographs. The position of catheters must be assessed on all radiographs, as serious complications can arise if catheters…