Segmentation is typically the first step in extracting useful information from medical images, where we determine the underlying anatomy. At UCNIA, we are developing new segmentation methodologies for different clinical applications with a focus on images containing pathology. We have developed segmentation schemes for healthy adults, neonatal (newborn) infants, and adults with diseases such as tumor and Multiple Sclerosis.
Simulated Brain Tumor MRI Database
Validation of segmentations of brain MRI require the use of a common database with known ground truth. For example, the validation database for the normal adult brain MRI provided by BrainWeb. However, there is a lack of ground truth validation data for pathological brain MRI such as those presenting tumor and edema.
We have made available synthetic brain MR images presenting tumor, that is generated by inserting pathology into a healthy brain MRI with known ground truth. The tumor and edema structures are generated following a physical model, which shows deformation due to tumor mass effect and infiltration due to both tumor and edema (if present). The synthetic brain tumor MR images generated using our method shows similar segmentation challenges as real brain tumor MRI.
Brain Lesion Analysis
Quantification, analysis and display of brain pathology such as white matter lesions as observed in MRI is important for diagnosis, monitoring of disease progression, improved understanding of pathological processes and for developing new therapies. The Utah Neuroimage Analysis Group develops new methodology for extraction of brain lesions from volumetric MRI scans and for characterization of lesion patterns over time. The images show white matter lesions (yellow) displayed with ventricles (blue) and transparent brain surface in a patient with an autoimmune disease (lupus). Lesions in white matter and possible correlations with cognitive deficits are also studied in patients with multiple sclerosis (MS), chronic depression, Alzheimer’s disease (AD) and in older persons.
Validation of segmentations of brain MRI require the use of a common database with known ground truth. For example, the validation database for the normal adult brain MRI provided by 
Quantification, analysis and display of brain pathology such as white matter lesions as observed in MRI is important for diagnosis, monitoring of disease progression, improved understanding of pathological processes and for developing new therapies. The Utah Neuroimage Analysis Group develops new methodology for extraction of brain lesions from volumetric MRI scans and for characterization of lesion patterns over time. The images show white matter lesions (yellow) displayed with ventricles (blue) and transparent brain surface in a patient with an autoimmune disease (lupus). Lesions in white matter and possible correlations with cognitive deficits are also studied in patients with multiple sclerosis (MS), chronic depression, Alzheimer’s disease (AD) and in older persons.