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Dr. Collins works on the use of computerized image processing techniques such as non-linear image registration and model-based segmentation to automatically identify structures within the human brain and to quantify anatomical variability. He investigates neuroscientific applications of three dimensional (3D) digital image processing methods for disease diagnosis, prognosis and image-guided surgery.

These techniques are applied to large databases of magnetic resonance (MR) data from normal subjects to quantify normal anatomical variability in pediatric, young adult and elderly populations. The techniques have also been used to automatically quantify global and regional brain atrophy in MS patients and to look at morphological changes associated with diseases such as schizophrenia and Alzheimer's dementia.

In image-guided neurosurgery (IGNS), these techniques provide the surgeon with computerized tools to assist in interpreting anatomical, functional and vascular image data, permitting the effective planning and execution of minimally invasive neurosurgical procedures. Automated atlasing is essential in IGNS for thalamotomy and pallidotomy in the treatment of Parkinson's disease, or temporal-lobe depth-electrode implantation in the diagnosis of epilepsy, since tissue targets in these procedures cannot be viewed directly on MR. Computerized atlasing minimizes trauma to the patient and allows resection of the smallest amount of brain tissue necessary for effective therapeutic treatment.

Keywords:

Neuroimaging
Magnetic Resonance Imaging (MRI)
Image Processing
Diagnosis and Treatment Systems
Data Mining
Segmentation
Biomarkers
Image-Guided Surgery