Development of a synthetic phantom for the selection of optimal scanning parameters in CAD-CT colonography

The aim of this paper is to present the development of a synthetic phantom that can be used for the selection of optimal scanning parameters in computed tomography (CT) colonography. In this paper we attempt to evaluate the influence of the main scanning parameters including slice thickness, reconstruction interval, field of view, table speed and radiation dose on the overall performance of a computer aided detection (CAD)–CTC system. From these parameters the radiation dose received a special attention, as the major problem associated with CTC is the patient exposure to significant levels of ionising radiation. To examine the influence of the scanning parameters we performed 51 CT scans where the spread of scanning parameters was divided into seven different protocols. A large number of experimental tests were performed and the results analysed. The results show that automatic polyp detection is feasible even in cases when the CAD–CTC system was applied to low dose CT data acquired with the following protocol: 13 mAs/rotation with collimation of 1.5 mm × 16 mm, slice thickness of 3.0 mm, reconstruction interval of 1.5 mm, table speed of 30 mm per rotation. The CT phantom data acquired using this protocol was analysed by an automated CAD–CTC system and the experimental results indicate that our system identified all clinically significant polyps (i.e. larger than 5 mm)

Digital Eversion of a Hollow Structure: An Application in Virtual Colonography

A new methodology is presented for digital eversion of a hollow structure. The digital eversion is advantageous for better visualization of a larger portion of the inner surface with preservation of geometric relationship and without time-consuming navigation. Together with other techniques, digital eversion may help improve screening, diagnosis, surgical planning, and medical education. Two eversion algorithms are proposed and evaluated in numerical simulation to demonstrate the feasibility of the approach

Area-preserving mapping of 3D ultrasound carotid artery images using density-equalizing reference map

Carotid atherosclerosis is a focal disease at the bifurcations of the carotid artery. To quantitatively monitor the local changes in the vessel-wall-plus-plaque thickness (VWT) and compare the VWT distributions for different patients or for the same patients at different ultrasound scanning sessions, a mapping technique is required to adjust for the geometric variability of different carotid artery models. In this work, we propose a novel method called density-equalizing reference map (DERM) for mapping 3D carotid surfaces to a standardized 2D carotid template, with an emphasis on preserving the local geometry of the carotid surface by minimizing the local area distortion. The initial map was generated by a previously described arc-length scaling (ALS) mapping method, which projects a 3D carotid surface onto a 2D non-convex L-shaped domain. A smooth and area-preserving flattened map was subsequently constructed by deforming the ALS map using the proposed algorithm that combines the density-equalizing map and the reference map techniques. This combination allows, for the first time, one-to-one mapping from a 3D surface to a standardized non-convex planar domain in an area-preserving manner. Evaluations using 20 carotid surface models show that the proposed method reduced the area distortion of the flattening maps by over 80% as compared to the ALS mapping method

One-sided transparency : a revolution in visualization.

Colorectal cancer is one of the leading causes of death in the world. Colonoscopy, the traditional procedure for detecting colorectal cancer, is very effective. It does have downsides, however - it is invasive, uncomfortable for the patient, and not available to some patients with certain conditions. Virtual colonoscopy has been developed in order to address these issues. A virtual colonoscopy (VC) is a non-invasive method for performing a colonoscopy by using medical imaging data to create a virtual representation of the colon. Previous virtual colonoscopy methods include fly-through, fly-over, flattening, and the unfolded cube method. Fly-through moves the camera through the inside of the colon, following a centerline from the length of the colon. Fly-over splits the colon into halves longitudinally, and flies a camera over each half. Flattening reduces the 3D colon model to a 2D image. The unfolded cube method flies a set of cameras along the centerline as in flythrough, but where flythrough had one camera looking along the centerline, the unfolded cube method presents views from six cameras. The six camera views are positioned in the pattern of an unfolded cube, which gives rise to the method’s name. This thesis will present a new method called one-sided transparency (OST). This is a method for visualizing virtual objects so that the interior surfaces can be viewed from the outside. OST has numerous improvements over existing VC methods, particularly when combined with fly-over methods. However, this thesis will also demonstrate that OST is not limited to fly-over nor even to VC, as it has applications in multiple fields. For quantitative evaluation, this thesis focused on comparing specific scenarios that OST excels in visualizing. Fly-through navigation has difficulties with polyps between haustral folds, and prior fly-over work had visual artifacts that degraded the quality of the final visualization. These and other specific cases are visualized using OST in order to highlight the power of this new technique. Additionally, the previous FO method had some significant drawbacks that are solved by the application of OST. These problems and their origins will be addressed, along with the way that OST solves them. This thesis will also explore potential applications for OST outside of VC. This will include a more general visualization of tubular objects. It will be shown that OST has the ability to highlight structural issues and deformities such as cracks and bumps. This has potential applications in medical fields outside of VC as well as in structural engineering. This will demonstrate OST’s usefulness as a general technique, even outside the context of VC. Finally, this thesis will present results regarding OST for VC. It will show that OST presents several advantages over previous VC methods. OST allows easier viewing of polyps in difficult locations and offers a more complete view of the colon. OST has a number of advantages over the existing fly-over method, including faster time-to-viewing, less sensitivity to centerline error, and improved accuracy in the separation of halves

Virtual colon unfolding for polyp detection

Master'sMASTER OF ENGINEERIN

Computer-aided detection of polyps in CT colonography

Master'sMASTER OF ENGINEERIN

Automatic colonic polyp detection using curvature analysis for standard and low dose CT data

Colon cancer is the second leading cause of cancer related deaths in the developed nations. Early detection and removal of colorectal polyps via screening is the most effective way to reduce colorectal cancer (CRC) mortality. Computed Tomography Colonography (CTC) or Virtual Colonoscopy (VC) is a rapidly evolving non-invasive technique and the medical community view this medical procedure as an alternative to the standard colonoscopy for the detection of colonic polyps. In CTC the first step for automatic polyp detection for 3D visualization of the colon structure and automatic polyp detection addresses the segmentation of the colon lumen. The segmentation of colon lumen is far from a trivial task as in practice many datasets are collapsed due to incorrect patient preparation or blockages caused by residual water/materials left in the colon. In this thesis a robust multi-stage technique for automatic segmentation of the colon is proposed tha t maximally uses the anatomical model of a generic colon. In this regard, the colon is reconstructed using volume by length analysis, orientation, length, end points, geometrical position in the volumetric data, and gradient of the centreline of each candidate air region detected in the CT data. The proposed method was validated using a total of 151 standard dose (lOOmAs) and 13 low-dose (13mAs-40mAs) datasets and the collapsed colon surface detection was always higher than 95% with an average of 1.58% extra colonic surface inclusion. The second major step of automated CTC attempts the identification of colorectal polyps. In this thesis a robust method for polyp detection based on surface curvature analysis has been developed and evaluated. The convexity of the segmented colon surface is sampled using the surface normal intersection, Hough transform, 3D histogram, Gaussian distribution, convexity constraint and 3D region growing. For each polyp candidate surface the morphological and statistical features are extracted and the candidate surface is classified as a polyp/fold structure using a Feature Normalized Nearest Neighbourhood classifier. The devised polyp detection scheme entails a low computational overhead (typically takes 3.60 minute per dataset) and shows 100% sensitivity for polyps larger than 10mm, 92% sensitivity for polyps in the range 5 to 10mm and 64.28% sensitivity for polyp smaller than 5mm. The developed technique returns in average 4.01 false positives per dataset. The patient exposure to ionising radiation is the major concern in using CTC as a mass screening technique for colonic polyp detection. A reduction of the radiation dose will increase the level of noise during the acquisition process and as a result the quality of the CT d a ta is degraded. To fully investigate the effect of the low-dose radiation on the performance of automated polyp detection, a phantom has been developed and scanned using different radiation doses. The phantom polyps have realistic shapes (sessile, pedunculated, and flat) and sizes (3 to 20mm) and were designed to closely approximate the real polyps encountered in clinical CT data. Automatic polyp detection shows 100% sensitivity for polyps larger than 10mm and shows 95% sensitivity for polyps in the range 5 to 10mm. The developed method was applied to CT data acquired at radiation doses between 13 to 40mAs and the experimental results indicate th a t robust polyp detection can be obtained even at radiation doses as low as 13mAs