Image Segmentation and Co-Registration in an Intraoperative Multimodal Imaging System (IMIS)

In this thesis, a new method for segmentation and co-registration of images from multiple modalities is presented. This approach has been tailored to meet the requirements of the Intra-operative Multimodal Imaging System (IMIS) being developed by Dr Mark Williams' lab in the department of Radiology and Medical Imaging at the University of Virginia. The IMIS can be used in a number of applications such as determining the location of primary and secondary carcinomas and sentinel lymph node biopsy. It consists of three imaging modalities- visible, near infrared fluorescence (NIRf), and gamma. The goal of my work is to segment the gamma images and co-register the gamma images with the visible and NIRf images. A series of filtering, binary morphology, edge detection, and active contour based techniques have been used for gamma image segmentation. Image co-registration is achieved with the help of two Attitude and Heading Reference System (AHRS) units.
This method has been tested in phantom studies and other laboratory settings and has shown promising results. Plans for small animal imaging and clinical trials in the operation room setting are underway.