Visualization and Detection of Colonic Polyps Joseph Marino, Arie Kaufman, Krishna Chaitanya Gurijala Stony Brook University, Stony Brook, NY 11794-4400 Introduction Virtual Colonoscopy Colon Flattening VC-OC Path Correlation Colorectal cancer is the 2nd leading cause of cancer death in the U.S. Detection and removal of adenomas is key for prevention and treatment Virtual colonoscopy (VC) as alternative to traditional screening Reconstruct virtual models that can be easily interrogated by humans Computer analysis for the detection of suspicious areas automatically Ray casting through CT data Isosurfacing transfer function Virtual view of colon wall from eye position inside the lumen More intuitive than 2D CT slices; mimics optical colonoscopy (OC) Automatic navigation via centerline Virtually slice colon open (from rectum to cecum) Conformally map surface to a plane (preserves shapes) Provide a correlation of the VC and optical colonoscopy (OC) paths Estimate OC path as nearly hugging corners shortest path Find corresponding points on paths within colon lumen cross section VC Centerline OC Path (estimate) Computer-Aided Detection Automatically detect suspicious areas that might contain a polyp Data preprocessing: - digital cleansing - segmentation - mesh extraction - conformal mesh flattening Use normalized direction vector for each point on the VC centerline Obtain plane which intersects colon lumen at this point Find point on estimated OC path which intersects this plane Compare locations on splines and with simulated VC-OC views Data Supine & prone abdomen CT scans Typically 500 axial slices each Waste material tagged with barium (appears brightly in scans) Digitally cleanse waste material Electronic Biopsy Translucent transfer function (integration of values along ray) Map higher density to red and map lower density to blue Differentiate between adenomas, hyperplastic polyps, and stool Adenomas have irregular high density structure 1) Render electronic biopsy image on the flattened mesh: 2) Perform clustering on the biopsy image to identify suspicious areas: Matching Points Original Cleansed VC Simulated OC Segment colon using air in lumen (black areas in scans) Generate centerline for navigation Extract colon wall as triangle mesh Proposed Work 3) Perform false positive reduction using shape-based analysis only at suspicious areas: Expand our analysis work for many VC components Analyze effectiveness of electronic biopsy and possible scoring system Anatomical feature detection Perform supine & prone registration Improve CAD work by integrating supine-prone registration Results on 188 datasets: 100 % sensitive & 3.2 FP/case Adenoma (pre-cancerous) Hyperplastic Polyp Retained Stool Supine Prone