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 …
This paper considers automatic clinical workflow description of full-length routine fetal anomaly ultrasound scans using deep learning approaches for spatio-temporal video analysis. Multiple architectures consisting of 2D and 2D + t CNN, LSTM, and …
We present a novel automated approach for detection of standardized abdominal circumference (AC) planes in fetal ultrasound built in a convolutional neural network (CNN) framework, called SonoEyeNet, that utilizes eye movement data of a sonographer …
In this paper, cell nuclei attributed relational graphs are extensively studied and comparatively analyzed for effective knowledge description and classification in H&E stained whole slide images of gastric cancer. This includes design and …
Automatic detection of necrosis in histological images is an interesting problem of digital pathology that needs to be addressed. Determination of presence and extent of necrosis can provide useful information for disease diagnosis and prognosis, and …