Uncovering hidden treasures: Mapping morphological changes in the differentiation of human mesenchymal stem cells to osteoblasts using deep learning.

Deep Learning (DL) is becoming an increasingly popular technology being employed in life sciences research due to its ability to perform complex and time-consuming tasks with significantly greater speed, accuracy, and reproducibility than human researchers - allowing them to dedicate their time to more complex tasks. One potential application of DL is to analyze cell images taken by microscopes. Quantitative analysis of cell microscopy images remain a challenge - with manual cell characterization requiring excessive amounts of time and effort.

Evaluation of RETRO-Mapping for electrophysiological features including direction of plane activity during atrial fibrillation using multipolar catheters in humans.

Introduction: A quantifiable, automated standard of analyzing heart rhythm has long eluded cardiologists due, in part, to the limitations in technology and the ability to analyze large electrogram datasets. In this proof-of-concept study, we propose new measures to quantify plane activity in atrial fibrillation (AF) using our Representation of Electrical Tracking of Origin (RETRO)-Mapping software.

Methods: We recorded 30 s segments of electrograms at the lower posterior wall of the left atrium using a 20-pole double loop catheter (AFocusII).

Automated multi-beat tissue Doppler echocardiography analysis using deep neural networks.

Tissue Doppler imaging is an essential echocardiographic technique for the non-invasive assessment of myocardial blood velocity. Image acquisition and interpretation are performed by trained operators who visually localise landmarks representing Doppler peak velocities. Current clinical guidelines recommend averaging measurements over several heartbeats.

Impact of chronic hypoxia on proximal pulmonary artery wave propagation and mechanical properties in rats.

Arterial stiffness and wave reflection are important components of the ventricular afterload. Therefore, we aimed to assess the arterial wave characteristics and mechanical properties of the proximal pulmonary arteries (PAs) in the hypoxic pulmonary hypertensive rat model. After 21 days in normoxic or hypoxic chambers (24 animals/group), animals underwent transthoracic echocardiography and PA catheterization with a dual-tipped pressure and Doppler flow sensor wire.

Doppler assessment of aortic stenosis: a 25-operator study demonstrating why reading the peak velocity is superior to velocity time integral.

Aims: Measurements with superior reproducibility are useful clinically and research purposes. Previous reproducibility studies of Doppler assessment of aortic stenosis (AS) have compared only a pair of observers and have not explored the mechanism by which disagreement between operators occurs. Using custom-designed software which stored operators' traces, we investigated the reproducibility of peak and velocity time integral (VTI) measurements across a much larger group of operators and explored the mechanisms by which disagreement arose.