gaze tracking

Spatio-Temporal Visual Attention Modelling of Standard Biometry Plane-Finding Navigation

We present a novel multi-task neural network called Temporal SonoEyeNet (TSEN) with a primary task to describe the visual navigation process of sonographers by learning to generate visual attention maps of ultrasound images around standard biometry …

Evaluation of Gaze Tracking Calibration for Longitudinal Biomedical Imaging Studies

Gaze tracking is a promising technology for studying the visual perception of clinicians during image-based medical exams. It could be used in longitudinal studies to analyze their perceptive process, explore human-machine interactions, and develop …

Evaluation of Gaze Tracking Calibration for Longitudinal Biomedical Imaging Studies

Gaze tracking is a promising technology for studying the visual perception of clinicians during image-based medical exams. It could be used in longitudinal studies to analyze their perceptive process, explore human-machine interactions, and develop …

Towards Capturing Sonographic Experience: Cognition-Inspired Ultrasound Video Saliency Prediction

For visual tasks like ultrasound (US) scanning, experts direct their gaze towards regions of task-relevant information. Therefore, learning to predict the gaze of sonographers on US videos captures the spatio-temporal patterns that are important for …

Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation

Recent automated medical image analysis methods have attained state-of-the-art performance but have relied on memory and compute-intensive deep learning models. Reducing model size without significant loss in performance metrics is crucial for time …

Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention

Image representations are commonly learned from class labels, which are a simplistic approximation of human image understanding. In this paper we demonstrate that transferable representations of images can be learned without manual annotations by …

Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps

We present a novel multi-task convolutional neural network called Multi-task SonoEyeNet (M-SEN) that learns to generate clinically relevant visual attention maps using sonographer gaze tracking data on input ultrasound (US) video frames so as to …