Focal Spot, Spring 1978

https://digitalcommons.wustl.edu/focal_spot_archives/1020/thumbnail.jp

Surface reconstruction for planning and navigation of liver resections

AbstractComputer-assisted systems for planning and navigation of liver resection procedures rely on the use of patient-specific 3D geometric models obtained from computed tomography. In this work, we propose the application of Poisson surface reconstruction (PSR) to obtain 3D models of the liver surface with applications to planning and navigation of liver surgery. In order to apply PSR, the introduction of an efficient transformation of the segmentation data, based on computation of gradient fields, is proposed. One of the advantages of PSR is that it requires only one control parameter, allowing the process to be fully automatic once the optimal value is estimated. Validation of our results is performed via comparison with 3D models obtained by state-of-art Marching Cubes incorporating Laplacian smoothing and decimation (MCSD). Our results show that PSR provides smooth liver models with better accuracy/complexity trade-off than those obtained by MCSD. After estimating the optimal parameter, automatic reconstruction of liver surfaces using PSR is achieved keeping similar processing time as MCSD. Models from this automatic approach show an average reduction of 79.59% of the polygons compared to the MCSD models presenting similar smoothness properties. Concerning visual quality, on one hand, and despite this reduction in polygons, clinicians perceive the quality of automatic PSR models to be the same as complex MCSD models. On the other hand, clinicians perceive a significant improvement on visual quality for automatic PSR models compared to optimal (obtained in terms of accuracy/complexity) MCSD models. The median reconstruction error using automatic PSR was as low as 1.03±0.23mm, which makes the method suitable for clinical applications. Automatic PSR is currently employed at Oslo University Hospital to obtain patient-specific liver models in selected patients undergoing laparoscopic liver resection

Computer- and robot-assisted Medical Intervention

Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practices easier and more efficient. This chapter focuses on such systems. It introduces the general field of Computer-Assisted Medical Interventions, its aims, its different components and describes the place of robots in that context. The evolutions in terms of general design and control paradigms in the development of medical robots are presented and issues specific to that application domain are discussed. A view of existing systems, on-going developments and future trends is given. A case-study is detailed. Other types of robotic help in the medical environment (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) are out of the scope of this chapter.Comment: Handbook of Automation, Shimon Nof (Ed.) (2009) 000-00

An Automatic Level Set Based Liver Segmentation from MRI Data Sets

A fast and accurate liver segmentation method is a challenging work in medical image analysis area. Liver segmentation is an important process for computer-assisted diagnosis, pre-evaluation of liver transplantation and therapy planning of liver tumors. There are several advantages of magnetic resonance imaging such as free form ionizing radiation and good contrast visualization of soft tissue. Also, innovations in recent technology and image acquisition techniques have made magnetic resonance imaging a major tool in modern medicine. However, the use of magnetic resonance images for liver segmentation has been slow when we compare applications with the central nervous systems and musculoskeletal. The reasons are irregular shape, size and position of the liver, contrast agent effects and similarities of the gray values of neighbor organs. Therefore, in this study, we present a fully automatic liver segmentation method by using an approximation of the level set based contour evolution from T2 weighted magnetic resonance data sets. The method avoids solving partial differential equations and applies only integer operations with a two-cycle segmentation algorithm. The efficiency of the proposed approach is achieved by applying the algorithm to all slices with a constant number of iteration and performing the contour evolution without any user defined initial contour. The obtained results are evaluated with four different similarity measures and they show that the automatic segmentation approach gives successful results

Augmentation of Articulate Data using 3D Image Analysis

Background: Recently, the development of information and communication technology (ICT) has been remarkable utilizing artificial intelligence (AI) technology with deep learning. Three-dimension (3-D) image analysis technology has developed using computerized tomography (CT), magnetic resonance imaging (MRI) and magnetic resonance angiography (MRA). Among them, SYNAPSE VINCENT system (Fujifilm, Japan) is known for its predominance. Patient and Method: The patient is a 52-year-old female with type 2 diabetes mellitus (T2DM), who was suspected to have space occupying lesion (SOL) in the right kidney. Method included the investigation of enhanced abdominal CT with analysis of SYNAPSE VINCENT. Results: The detail analysis showed some findings as follows: i) coronal view of bilateral kidney shows well-enhanced left adrenal tumour, no apparent of right renal tumour, and atrophy of renal cortex, ii) the image rotated 30 degrees showed same findings, iii) the image rotated 180 degrees also showed atrophy of reverse side of right kidney. Discussion: In this case, the background of the atrophy of renal cortex has not been apparent, but it might be from diabetic nephropathy (DN). The application of VINCENT has expanded to various organs, such as liver, pancreas, biliary tract, and others, expecting augmentation of articulate data using 3D image analysis

Focal Spot, Winter 1984/85

https://digitalcommons.wustl.edu/focal_spot_archives/1039/thumbnail.jp

Focal Spot, Fall/Winter 1994

https://digitalcommons.wustl.edu/focal_spot_archives/1068/thumbnail.jp

Recent finding and new technologies in nephrolithiasis: a review of the recent literature

This review summarizes recent literature on advances regarding renal and ureteral calculi, with particular focus in areas of recent advances in the overall field of urolithiasis. Clinical management in everyday practice requires a complete understanding of the issues regarding metabolic evaluation and subgrouping of stone-forming patients, diagnostic procedures, effective treatment regime in acute stone colic, medical expulsive therapy, and active stone removal. In this review we focus on new perspectives in managing nephrolitihiasis and discuss recentadvances, including medical expulsive therapy, new technologies, and refinements of classical therapy such as shock wave lithotripsy, give a fundamental modification of nephrolithiasis management. Overall, this field appears to be the most promising, capable of new developments in ureterorenoscopy and percutaneous approaches. Further improvements are expected from robotic-assisted procedures, such as flexible robotics in ureterorenoscopy

Focal Spot, Summer 2002

https://digitalcommons.wustl.edu/focal_spot_archives/1091/thumbnail.jp