Supervised training of deep learning models requires large labeled datasets. There is a
growing interest in obtaining such datasets for medical image analysis applications …

Rationale and Objectives. To examine a statistical validation method based on the spatial
overlap between two sets of segmentations of the same anatomy. Materials and Methods …

Characterizing the performance of image segmentation approaches has been a persistent
challenge. Performance analysis is important since segmentation algorithms often have …

Fetal magnetic resonance imaging (MRI) examinations have become well‐established
procedures at many institutions and can serve as useful adjuncts to ultrasound (US) exams …

Objective. To investigate the effects of early experience on brain function and structure.
Methods. A randomized clinical trial tested the neurodevelopmental effectiveness of the …

Background. Long-term studies of the outcome of very prematurely born infants have clearly
documented that the majority of such infants have significant motor, cognitive, and …

Long computation times of non-linear (ie accounting for geometric and material non-
linearity) biomechanical models have been regarded as one of the key factors preventing …

The watershed transform has interesting properties that make it useful for many different
image segmentation applications: it is simple and intuitive, can be parallelized, and always …

An automated brain tumor segmentation method was developed and validated against
manual segmentation with three-dimensional magnetic resonance images in 20 patients …

Placental insufficiency with fetal intrauterine growth restriction (IUGR) is an important cause
of perinatal mortality and morbidity and is subsequently associated with significant …