Focal Spot, Fall/Winter 1996

https://digitalcommons.wustl.edu/focal_spot_archives/1071/thumbnail.jp

High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures

Compressive sensing (CS) describes how sparse signals can be accurately reconstructed from many fewer samples than required by the Nyquist criterion. Since MRI scan duration is proportional to the number of acquired samples, CS has been gaining significant attention in MRI. However, the computationally intensive nature of CS reconstructions has precluded their use in routine clinical practice. In this work, we investigate how different throughput-oriented architectures can benefit one CS algorithm and what levels of acceleration are feasible on different modern platforms. We demonstrate that a CUDA-based code running on an NVIDIA Tesla C2050 GPU can reconstruct a 256 × 160 × 80 volume from an 8-channel acquisition in 19 seconds, which is in itself a significant improvement over the state of the art. We then show that Intel's Knights Ferry can perform the same 3D MRI reconstruction in only 12 seconds, bringing CS methods even closer to clinical viability

Visual Perception and Cognition in Image-Guided Intervention

Surgical image visualization and interaction systems can dramatically affect the efficacy and efficiency of surgical training, planning, and interventions. This is even more profound in the case of minimally-invasive surgery where restricted access to the operative field in conjunction with limited field of view necessitate a visualization medium to provide patient-specific information at any given moment. Unfortunately, little research has been devoted to studying human factors associated with medical image displays and the need for a robust, intuitive visualization and interaction interfaces has remained largely unfulfilled to this day. Failure to engineer efficient medical solutions and design intuitive visualization interfaces is argued to be one of the major barriers to the meaningful transfer of innovative technology to the operating room. This thesis was, therefore, motivated by the need to study various cognitive and perceptual aspects of human factors in surgical image visualization systems, to increase the efficiency and effectiveness of medical interfaces, and ultimately to improve patient outcomes. To this end, we chose four different minimally-invasive interventions in the realm of surgical training, planning, training for planning, and navigation: The first chapter involves the use of stereoendoscopes to reduce morbidity in endoscopic third ventriculostomy. The results of this study suggest that, compared with conventional endoscopes, the detection of the basilar artery on the surface of the third ventricle can be facilitated with the use of stereoendoscopes, increasing the safety of targeting in third ventriculostomy procedures. In the second chapter, a contour enhancement technique is described to improve preoperative planning of arteriovenous malformation interventions. The proposed method, particularly when combined with stereopsis, is shown to increase the speed and accuracy of understanding the spatial relationship between vascular structures. In the third chapter, an augmented-reality system is proposed to facilitate the training of planning brain tumour resection. The results of our user study indicate that the proposed system improves subjects\u27 performance, particularly novices\u27, in formulating the optimal point of entry and surgical path independent of the sensorimotor tasks performed. In the last chapter, the role of fully-immersive simulation environments on the surgeons\u27 non-technical skills to perform vertebroplasty procedure is investigated. Our results suggest that while training surgeons may increase their technical skills, the introduction of crisis scenarios significantly disturbs the performance, emphasizing the need of realistic simulation environments as part of training curriculum

Flow and pressure measurement using phase-contrast MRI : experiments in stenotic phantom models.

Peripheral Arterial Disease (PAD) is a progressive atherosclerotic disorder which is defined as any pathologic process obstructing the blood flow of the arteries supplying the lower extremities. Moderate stenoses mayor may not be hemodynamically significant, and intravascular pressure measurements have been recommended to evaluate whether these lesions are clinically significant. Phase-contrast MRI (PC-MRI) provides a powerful and non-invasive method to acquire spatially registered blood velocity. The velocity field, then, can be used to derive other clinically useful hemodynamic parameters, such as blood flow and blood pressure gradients. Herein, a series of detailed experiments are reported for the validation of MR measurements of steady and pulsatile flows with stereoscopic particle image velocimetry (SPIV). Agreement between PC-MRI and SPIV was demonstrated for both steady and pulsatile flow measurements at the inlet by evaluating the linear regression between the two methods, which showed a correlation coefficient of\u3e 0.99 and\u3e 0.96 for steady and pulsatile flows, respectively. Experiments revealed that the most accurate measures of flow by PC-MRI are found at the throat of the stenosis (error \u3c 5% for both steady and pulsatile mean flows). The flow rate error distal to the stenosis was shown to be a function of narrowing severity. Furthermore, pressure differences across an axisymmetric stenotic phantom model were estimated by solving the pressure-Poisson equation (iterative method) and a non-iterative method based on harmonics-based orthogonal projection using PC-MRI velocity data. Results were compared with the values obtained from other techniques including SPIV, computational fluid dynamic (CFD) simulations, and direct pressure measurements. Using the pressure obtained from CFD as the ground truth and PC-MRI velocity data as the input, the relative error in pressure drop for iterative and non-iterative techniques were 13.1 % and 12.5% for steady flow, 4.0% and 22.1 % for pulsatile flow at peak-systole, and 194.5% and 155.2% at end-diastole, respectively. It was concluded that pressure drop calculation using PC-MRI is more promising for steady cases and pulsatile cases at peak-systole compared to pulsatile flow cases at end-diastole