Drishti, a volume exploration and presentation tool

Among several rendering techniques for volumetric data, direct volume rendering is a powerful visualization tool for a wide variety of applications. This paper describes the major features of hardware based volume exploration and presentation tool - Drishti. The word, Drishti, stands for vision or insight in Sanskrit, an ancient Indian language. Drishti is a cross-platform open-source volume rendering system that delivers high quality, state of the art renderings. The features in Drishti include, though not limited to, production quality rendering, volume sculpting, multi-resolution zooming, transfer function blending, profile generation, measurement tools, mesh generation, stereo/anaglyph/crosseye renderings. Ultimately, Drishti provides an intuitive and powerful interface for choreographing animations

Techniques, Clinical Applications and Limitations of 3D Reconstruction in CT of the Abdomen

Enhanced z-axis coverage with thin overlapping slices in breath-hold acquisitions with multidetector CT (MDCT) has considerably enhanced the quality of multiplanar 3D reconstruction. This pictorial essay describes the improvements in 3D reconstruction and technical aspects of 3D reconstruction and rendering techniques available for abdominal imaging. Clinical applications of 3D imaging in abdomen including liver, pancreaticobiliary system, urinary and gastrointestinal tracts and imaging before and after transplantation are discussed. In addition, this article briefly discusses the disadvantages of thin-slice acquisitions including increasing numbers of transverse images, which must be reviewed by the radiologist

Coronary Artery Segmentation and Motion Modelling

Conventional coronary artery bypass surgery requires invasive sternotomy and the use of a cardiopulmonary bypass, which leads to long recovery period and has high infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery based on image guided robotic surgical approaches have been developed to allow the clinicians to conduct the bypass surgery off-pump with only three pin holes incisions in the chest cavity, through which two robotic arms and one stereo endoscopic camera are inserted. However, the restricted field of view of the stereo endoscopic images leads to possible vessel misidentification and coronary artery mis-localization. This results in 20-30% conversion rates from TECAB surgery to the conventional approach. We have constructed patient-specific 3D + time coronary artery and left ventricle motion models from preoperative 4D Computed Tomography Angiography (CTA) scans. Through temporally and spatially aligning this model with the intraoperative endoscopic views of the patient's beating heart, this work assists the surgeon to identify and locate the correct coronaries during the TECAB precedures. Thus this work has the prospect of reducing the conversion rate from TECAB to conventional coronary bypass procedures. This thesis mainly focus on designing segmentation and motion tracking methods of the coronary arteries in order to build pre-operative patient-specific motion models. Various vessel centreline extraction and lumen segmentation algorithms are presented, including intensity based approaches, geometric model matching method and morphology-based method. A probabilistic atlas of the coronary arteries is formed from a group of subjects to facilitate the vascular segmentation and registration procedures. Non-rigid registration framework based on a free-form deformation model and multi-level multi-channel large deformation diffeomorphic metric mapping are proposed to track the coronary motion. The methods are applied to 4D CTA images acquired from various groups of patients and quantitatively evaluated

Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Fiber identification of braided composites using micro-computed tomography

Braided composites contain interwoven fibers that are embedded in a matrix material. Advanced measurement methods are required to accurately measure and characterize braided composites due to their interwoven composition. Micro-computed tomography (μCT) is an X-ray based measurement method that allows for the internal structure of objects to be examined. High-resolution μCT of braided composites allows for their internal geometry to be accurately measured. Braid samples were measured with a voxel size of 1.0 μm3, which resulted in a field of view of 4.904 x 4.904 x 3.064 mm3. With this field of view, individual fibers within the braid yarns could be identified and measured. The scientific visualization software package Avizo and the XFiber extension was used to identify and measure braid yarn fibers from the collected μCT measurements. Fiber properties such as orientation angles (ϕ and θ), curved fiber length, tortuosity, and fiber diameter were obtained. Additionally, finite element mesh geometries of the braid yarns within a braided structure were created. The presented methodology provides a roadmap for the accurate modeling of braided composite unit cell geometries using high-resolution μCT data.Natural Sciences and Engineering Research Council (NSERC) Canada RGPIN- 2018-05899. CMC Microsystems provided the software used in this study

Visualisation of curved tubular structures in medical databases: An application to virtual colonoscopy

Medical conditions affecting the colon are problematic to diagnose due to the difficulty in examining this particular internal organ. To date, the most widely used approach is to perform a colonoscopy; a procedure in which a small camera is inserted into the colon to examine its surface. This procedure is unpleasant and potentially dangerous for the patient, and is expensive and time consuming for the hospital. As a result, patients at risk of developing the conditions are not always screened as often as would be desirable. Over the last few years a new approach known as virtual colonoscopy has been gaining popularity. The method uses information from a CT scan to reconstruct a 3D model of the colon which can then be examined without the patient needing to undergo a colonoscopy. This approach is now commonly used when screening for polyps (an indication of colon cancer) but can not be so easily used on conditions such as Inflammatory Bowel Disease (IBD) where information beyond the shape of the surface is required. This thesis forms part of a larger project which aims to diagnose conditions such as IBD by using image processing algorithms on CT data and presenting the results to the user in an easy to interpret way. Specifically we are concerned with this visualisation stage of the system and so have developed a new visualisation approach which we call Volumetric CPR. This can be used to supplement the more traditional virtual flythrough visualisation and is applicable to IBD detection as well as screening for polyps. Our technique builds on the concept of Curved Planar Reformation (CPR), which has proved to be a practical and widely used tool for the visualisation of curved tubular structures within the human body. It has been useful in medical procedures involving the examination of blood vessels and the spine. However, it is more difficult to use it for structures such as the colon because abnormalities are smaller relative to the size of the structure and may not have such distinct density and shape characteristics. Our new approach improves on this situation by using volume rendering for hollow regions of the structure and standard CPR, for the surrounding tissue. This effectively combines grey scale contextual information with detailed colour information from the area of interest. The approach is successfully used with each of the standard CPR types and the resulting images are promising as an alternative for virtual colonoscopy. We also demonstrate how systems can effectively utilize this new visualisation in order to convey maximum information to the user. We show how overlays can be used to present surface coverage data and how sophisticated lighting models can improve the users understanding of the 3D structure. We also present details of how to integrate our visualisation into existing systems and work flows

Computerized detection of noncalcified plaques in coronary CT angiography: Evaluation of topological soft gradient prescreening method and luminal analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135084/1/mp5958.pd