Machine Learning

Transforming obstetric ultrasound into data science using eye tracking, voice recording, transducer motion and ultrasound video

Ultrasound is the primary modality for obstetric imaging and is highly sonographer dependent. Long training period, insufficient recruitment and poor retention of sonographers are among the global challenges in the expansion of ultrasound use. For …

Machine Learning-based Analysis of Operator Pupillary Response to Assess Cognitive Workload in Clinical Ultrasound Imaging

Introduction Pupillometry, the measurement of eye pupil diameter, is a well-established and objective modality correlated with cognitive workload. In this paper, we analyse the pupillary response of ultrasound imaging operators to assess their …

OC10.11: The data science of obstetric ultrasound: automatic analysis of full‐length anomaly scans using machine learning algorithms

BibTex @article{doi:10.1002/uog.22275, author = {Drukker, L. and Sharma, H. and Droste, R. and Noble, J.A. and Papageorghiou, A.T.}, title = {OC10.11: The data science of obstetric ultrasound: automatic analysis of full-length anomaly scans using machine learning algorithms}, journal = {Ultrasound in Obstetrics \& Gynecology}, volume = {56}, number = {S1}, pages = {31-31}, doi = {10.1002/uog.22275}, url = {https://obgyn.onlinelibrary.wiley.com/doi/abs/10.1002/uog.22275}, eprint = {https://obgyn.onlinelibrary.wiley.com/doi/pdf/10.1002/uog.22275}, year = {2020} }

Discovering Salient Anatomical Landmarks by Predicting Human Gaze

Anatomical landmarks are a crucial prerequisite for many medical imaging tasks. Usually, the set of landmarks for a given task is predefined by experts. The landmark locations for a given image are then annotated manually or via machine learning …

Monitoring Sonographer Performance: The Perception Ultrasound by Learning Sonographer Experience (PULSE) study

Appearance-based necrosis detection using textural features and SVM with discriminative thresholding in histopathological whole slide images

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 …