Automated Detection and Segmentation of Large Lesions in CT Colonography

Computerized tomographic colonography is a minimally invasive technique for the detection of colorectal polyps and carcinoma. Computer-aided diagnosis (CAD) schemes are designed to help radiologists locating colorectal lesions in an efficient and accurate manner. Large lesions are often initially detected as multiple small objects, due to which...

Computer-Aided Detection of Polyps in CT Colonography Using Logistic Regression

We present a computer-aided detection (CAD) system for computed tomography colonography that orders the polyps according to clinical relevance. TheCADsystem consists of two steps: candidate detection and supervised classification. The characteristics of the detection step lead to specific choices for the classification system. The candidates are...

Efficient seeding and defragmentation of curvature streamlines for colonic polyp detection

Many computer aided diagnosis (CAD) schemes have been developed for colon cancer detection using Virtual Colonoscopy (VC). In earlier work, we developed an automatic polyp detection method integrating flow visualization techniques, that forms part of the CAD functionality of an existing Virtual Colonoscopy pipeline. Curvature streamlines were...

Classifying CT Image Data Into Material Fractions by a Scale and Rotation Invariant Edge Model

A fully automated method is presented to classify 3-D CT data into material fractions. An analytical scale-invariant description relating the data value to derivatives around Gaussian blurred step edges—arch model—is applied to uniquely combine robustness to noise, global signal fluctuations, anisotropic scale, noncubic voxels, and ease of use...