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The accurate and automated measuring of durations of certain human embryo stages is important to assess embryo viability and predict its clinical outcomes in in vitro fertilization (IVF). In this work, we present a multi-level embryo stage classification method to identify the number of cells at every time point of a time-lapse microscopy video of early(More)
This paper presents a general framework for analyzing structural and radiometric asymmetry in brain images. In a healthy brain, the left and right hemispheres are largely symmetric across the mid-sagittal plane. Brain tumors may belong to one or both of the following categories: mass-effect, in which the diseased tissue displaces healthy tissue; and(More)
In this paper, we present a Bayesian framework for both generating inter-subject large deformation transformations between two multi-modal image sets of the brain and for forming multi-class brain atlases. In this framework, the estimated transformations are generated using maximal information about the underlying neuroanatomy present in each of the(More)
BACKGROUND There is still a considerable controversy regarding optimal treatment for patients with acute type B aortic dissection. Patients with complicated disease are particularly challenging for cardiovascular treatment. Early surgery for acute dissections of the descending aorta with life-threatening complications is known to carry a high mortality.(More)
BACKGROUND Farm milk consumption has been identified as an exposure that might contribute to the protective effect of farm life on childhood asthma and allergies. The mechanism of action and the role of particular constituents of farm milk, however, are not yet clear. OBJECTIVE We sought to investigate the farm milk effect and determine responsible milk(More)
The construction of population atlases is a key issue in medical image analysis, and particularly in brain mapping. Large sets of images are mapped into a common coordinate system to study intra-population variability and inter-population differences, to provide voxel-wise mapping of functional sites, and to facilitate tissue and object segmentation via(More)
Many medical image analysis problems that involve multi-modal images lend themselves to solutions that involve class posterior density function images. This paper presents a method for large deformation exemplar class posterior density template estimation. This method generates a representative anatomical template from an arbitrary number of topologically(More)
This paper addresses the challenging problem of statistics on images by describing average and variability. We describe computational anatomy tools for building 3-D and spatio-temporal 4-D atlases of volumetric image data. The method is based on the previously published concept of unbiased atlas building, calculating the nonlinear average image of a(More)
This paper presents a Bayesian framework for generating inverse-consistent inter-subject large deformation transformations between two multi-modal image sets of the brain. In this framework, the estimated transformations are generated using the maximal information about the underlying neuroanatomy present in each of the different modalities. This modality(More)