KEYWORDS: Image segmentation, 3D image processing, 3D metrology, Artificial intelligence, 3D displays, 3D modeling, Computed tomography, Photovoltaics, Bone, Visualization
The developmental dysplasia of the hip (DDH) is a congenital malformation affecting the proximal femurs and acetabulum that are subluxatable, dislocatable, and dislocated. Early diagnosis and treatment is important because failure to diagnose and improper treatment can result in significant morbidity. In this paper, we designed and implemented a computer aided system for the diagnosis and treatment planning of this disease. With the design, the patient received CT (computed tomography) or MRI (magnetic resonance imaging) scan first. A mixture-based PV partial-volume algorithm was applied to perform bone segmentation on CT image, followed by three-dimensional (3D) reconstruction and display of the segmented image, demonstrating the special relationship between the acetabulum and femurs for visual judgment. Several standard procedures, such as Salter procedure, Pemberton procedure and Femoral Shortening osteotomy, were simulated on the screen to rehearse a virtual treatment plan. Quantitative measurement of Acetabular Index (AI) and Femoral Neck Anteversion (FNA) were performed on the 3D image for evaluation of DDH and treatment plans. PC graphics-card GPU architecture was exploited to accelerate the 3D rendering and geometric manipulation. The prototype system was implemented on PC/Windows environment and is currently under clinical trial on patient datasets.
In this paper, we proposed a new efficient implementation for simulation of surgery planning for congenital aural
atresia. We first applied a 2-level image segmentation schema to classify the inner ear structures. Based on it, several
3D texture volumes were generated and sent to graphical pipeline on a PC platform. By exploiting the texturingmapping
capability on the PC graphics/video board, a 3D image was created with high quality showing the accurate
spatial relationships of the complex surgical anatomy of congenitally atretic ears. Furthermore, we exploited the
graphics hardware-supported per-fragment function to perform the geometric clipping on 3D volume data to
interactively simulate the procedure of surgical operation. The result was very encouraging.
One of the most important tasks for virtual endoscopy is path planning for viewing the lumen of hollow organs. For geometry complex objects, for example the lungs, it remains an unsolved problem. While alternative visualization modes have been proposed, for example, cutting and flattening the hollow wall, a skeleton of the lumen is still necessary as a reference for the cutting. A general-purpose skeletonization algorithm often generates redundant skeletons because of the local shape variation. In this study, a multistage skeletonization method for tree-like volumes, such as airway system, blood vessels, and colon, was presented. By appropriately defining the distance between voxels, the distance to the root from each voxel in the volume can be effectively determined with means of region growing techniques. The end points of all branches and the shortest path from each end point to the root can be extracted based on this distance map. A post-processing algorithm is applied to the shortest paths to remove redundant ones and to centralize the remained ones. The skeleton generated is one-voxel wide, along which every branch of the 'tree' can be viewed. For effectively processing volume of large size, a modified multiresolution analysis was also developed to scale down the binary segmented volume. Tests on airway, vessel, and colon dataset were promising.
Computed tomography (CT) based virtual cystoscopy (VC) has been studied as a potential tool for screening bladder cancer. It is accurate in localizing tumor of size larger than 1 cm and less expensive, as compared to fiberoptic cystoscopy. However, it is invasive and difficult to perform due to using Foley catheter for bladder insufflating with air. In a previous work, we investigated a magnetic resonance imaging (MRI) based VC scheme with urine as a natural contrast solution, in which a MRI acquisition protocol and an adaptive segmentation method were utilized. Both bladder lumen and wall were successfully delineated. To suppress motion artifact and insight pathological change on the bladder wall images, a multi-scan MRI scheme was presented in this study. One transverse and another coronal acquisitions of T1-weighted that cover the whole bladder were obtained twice, at one time the bladder is full of urine and at another time it is near the empty. Four bladder volumes extracted from those 4 datasets were registered first using a flexible three- dimensional (3D) registration algorithm. Then, associated 4 lumen surfaces were viewed simultaneously with the help of an interactive 3D visualization system. This MRI-based VC was tested on volunteers and demonstrated the feasibility to mass screening for bladder cancer.
We have designed and implemented a prototype system to aid in the surgical repair of congenital aural atresia. A two- level segmentation algorithm was first developed to separate tissues of similar intensity or low tissue contrast. Then an interactive visualization modular was built to display the labeled tissues. The system allows a 3-stage interactive planning in which positioning, marking and drilling simulates the surgical operation of congenital atresia repair. A voxel-based volume CSG operation was implemented to ensure the efficiency of interactive planning. Six patients with congenital aural atresia underwent virtual planning in preparation for surgery. This technique has proved to be a valuable planning tool, with the potential for virtual representation of the surgical reconstruction.
Residual stool and fluid and wall collapses are problematic for virtual colonoscopy. Electronic colon cleansing techniques combining both bowel preparation and image processing were developed to segment the colon lumen from the abdominal computed tomographic (CT) images. This paper describes our bowel preparation and image segmentation techniques and presents some preliminary results. A feasibility study using magnetic resonance imaging (MRI) is also reported.
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