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

… *SK Warfield is with Harvard Medical School and the Department of Radiology of Brigham
and … Kikinis, and SK Warfield, “Three validation metrics for automated probabilistic image …

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. The …

… Warfield's research interests in the field of medical image computing have focused on the
development of innovative algorithms to address the requirements of clinical care and …

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

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 …

… Kikinis, and SK Warfield are with the Surgical Planning Laboratory, Brigham and Women’s …
threshold are considered outliers and removed, generating the corrected skeleton Sk corr …

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 …

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

In the human brain, the morphology of cortical gyri and sulci is complex and variable among
individuals, and it may reflect pathological functioning with specific abnormalities observed …