Search Results for author:
Found 4 papers, 1 papers with code
FetalNet: Multi-task Deep Learning Framework for Fetal Ultrasound Biometric Measurements
The main goal in fetal ultrasound scan video analysis is to find proper standard planes to measure the fetal head, abdomen and femur.
Convolutional Neural Networks in Orthodontics: a review
Convolutional neural networks (CNNs) are used in many areas of computer vision, such as object tracking and recognition, security, military, and biomedical image analysis.
Spontaneous preterm birth prediction using convolutional neural networks
Based on the conducted results and model efficiency, we decided to extend U-Net by adding a parallel branch for classification task.
Estimation of preterm birth markers with U-Net segmentation network
To achieve this goal, we propose to first use a deep neural network architecture for segmenting prenatal ultrasound images and then automatically extract two biophysical ultrasound markers, cervical length (CL) and anterior cervical angle (ACA), from the resulting images.
