Incorporating 3D virtual anatomy into the medical curriculum

The introduction of the Visible Human Project by Ackerman in 1995, described in the seminal paper in 1996, brought a promise to anatomists that these two frozen, milled, and digitized cadavers--the Visible Male and Female--would revolutionize anatomy teaching by providing the most complete and detailed anatomical images ever. This vision could be compared to the proverbial "man on the moon" program for medical education and has proven to be much more challenging than expected. Although the ramifications of this project are not of the same scale as the shock created five centuries ago by the Padua physician Andreas Vesalius when he challenged the ancient Greek physician Galen's description of the human body, the original interest created by the availability of the Visible Human data was enormous

An adaptive speed term based on homogeneity for level-set segmentation

We tested on an edge map computed from a local homogeneity measurement, which is a potential replacement for the traditional gradient-based edge map in level-set segmentation. In existing level-set methods, the gradient information is used as a stopping criteria for curve evolution, and also provides the attracting force to the zero level-set from the target boundary. However, in a discrete implementation, the gradient-based term can never fully stop the level-set evolution even for ideal edges, leakage is often unavoidable. Also the effective distance of the attracting force and blurring of edges become a trade-off in choosing the shape and support of the smoothing filter. The proposed homogeneity measurement provides easier and more robust edge estimation, and the possibility of fully stopping the level-set evolution. The homogeneity term decreasing from a homogenous region to the boundary, which dramatically increases the effective distance of the attracting force and also provides additional measurement of the overall approximation to the target boundary. Therefore, it provides a reliable criteria of adaptively changing the advent speed. By using this term, the leakage problem was avoided effectively in most cases compared to traditional level-set methods. The computation of the homogeneity is fast and its extension to the 3D case is straightforward

Multi-Scale Visual Analysis of Trauma Injury

We develop a multi-scale high-fidelity biomechanical and physiologically based modeling tools for trauma (ballistic/impact and blast) injury to brain, lung and spinal cord for resuscitation, treatment planning and design of personnel protection. Several approaches have been used to study blast and ballistic/impact injuries. Dummy containing pressure sensors and synthetic phantoms of human organs have been used to study bomb blast and car crashes. Large animals like pigs also have been equipped with pressure sensors exposed to blast waves. But these methods do not provide anatomically and physiologically, full optimization of body protection design and require animal sacrifice. Anatomy and medical image-based high-fidelity computational modeling can be used to analyze injury mechanisms and to optimize the design of body protection. This paper presents novel approach of coupled computational fluid dynamics and computational structures dynamics to simulate fluid (air, cerebrospinal fluid)–solid (cranium, brain tissue) interaction during ballistic/blast impact. We propose a trauma injury simulation pipeline concept staring from anatomy and medical image-based high-fidelity 3D geometric modeling, extraction of tissue morphology, generation of computational grids, multi-scale biomechanical and physiological simulations, and data visualization

Segmentation and Evaluation of Adipose Tissue from Whole Body MRI Scans

Accurate quantification of total body and the distribution of regional adipose tissue using manual segmentation is a challenging problem due to the high variation between manual delineations. Manual segmentation also requires highly trained experts with knowledge of anatomy. We present a hybrid segmentation method that provides robust delineation results for adipose tissue from whole body MRI scans. A formal evaluation of accuracy of the segmentation method is performed. This semi-automatic segmentation algorithm reduces significantly the time required for quantification of adipose tissue, and the accuracy measurements show that the results are close to the ground truth obtained from manual segmentations

New views of male pelvic anatomy: Role of computer-generated 3D images

There is considerable controversy concerning the role of cadaveric dissection in teaching gross anatomy and the potential of using 3D computer-generated images to substitute for actual laboratory dissections. There are currently few high-quality 3D virtual models of anatomy available to evaluate the utility of computer-generated images. Existing 3D models are frequently of structures that are easily examined in three dimensions by removal from the cadaver, i.e., the heart, skull, and brain. We have focused on developing a 3D model of the pelvis, a region that is conceptually difficult and relatively inaccessible for student dissection. We feel students will benefit tremendously from 3D views of the pelvic anatomy. We generated 3D models of the male pelvic anatomy from hand-segmented color Visible Human Male cryosection data, reconstructed and visualized by Columbia University's in-house 3D Vesalius Visualizer.1 These 3D models depict the anatomy of the region in a realistic true-to-life color and texture. They can be used to create 3D anatomical scenes, with arbitrary complexity, where the component anatomical structures are displayed in correct 3D anatomical relationships. Moreover, a sequence of 3D scenes can be defined to simulate actual dissection. Structures can be added in a layered sequence from the bony framework to build from the "inside-out" or disassembled much like a true laboratory dissection from the "outside-in." These 3D reconstructed anatomical models can provide views of the structures from new perspectives and have the potential to improve understanding of the anatomical relationships of the pelvic region (http://www.cellbiology.lsuhsc.edu/People/Faculty/Venuti_Figures/movie_index.html)

A General Class of Heuristics for Minimum Weight Perfect Matching and Fast Special Cases with Doubly and Triply Logarithmic Errors

We give a class of heuristic algorithms for minimum weight perfect matching on a complete edgeweighted graph K(V) satisfying the triangle inequality, where V is a set of an even number, n, of vertices.This class is a generalization of the Onethird heuristics, the hypergreedy heuristic, and it possibly employs any given exact or approximate perfect matching algorithm as an auxiliary heuristic to an appropriate subgraph of K(V)

Improving statistics for hybrid segmentation of high-resolution multichannel images

High-resolution multichannel textures are difficult to characterize with simple statistics and the high level of detail makes the selection of a particular contour using classical gradient-based methods not effective. We have developed a hybrid method that combines fuzzy connectedness and Voronoi diagram classification for the segmentation of color and multichannel objects. The multi-step classification process relies on homogeneity measures derived from moment statistics and histogram information. These color features have been optimized to best combine individual channel information in the classification process. The segmentation initialization requires only a set of interior and exterior seed points, minimizing user intervention and the influence of the initialization on the overall quality of the results. The method was tested on volumes from the Visible Human and on brain multi-protocol MRI data sets. The hybrid segmentation produced robust, rapid and finely detailed contours with good visual accuracy. The addition of quantized statistics and color histogram distances as classification features improved the robustness of the method with regards to initialization when compared to our original implementation

Evaluation of automated segmentation of hip joint in revision arthroplasty

We present a case of a 72-year-old female patient with a history of degenerative hip joint disease for whom a custom-made prosthesis—an acetabulum cage—was designed. With the growing number of total hip arthroplasty (THA) operations and the rapid development of technology, biology, and tissue bioengineering, there is a market to develop new artificial hip joints. The quality of the custom made prosthesis depends on the quality of segmentation to delineate accurately patient’s anatomy. The error of segmentation may propagate to the overall error of the final prosthesis. We evaluate an in-house segmentation method, that was used in the design of the custom made prosthesis, and a commercial segmentation method, using qualitative and quantitative approaches

Automatic Misalignment Correction in Neuroimages Using Surface Symmetry Priors

Many brain imaging procedures require the careful alignment of different sets of images obtained in the same individual. The available automatic methods for brain alignment are susceptible to improvement. This paper discusses briefly a new automatic method to reinstall the tilted orientation of head images, using surface symmetry as a prior

Employing Symmetry Features for Automatic Misalignment Correction in Neuroimages

A novel method to automatically compute the symmetry plane and to correct the 3D orientation of neuro-images is presented. In acquisition of neuroimaging scans, the lack of perfect alignment of a patient's head makes it challenging to evaluate brain images. By deploying a shape-based criterion, the symmetry plane is defined as a plane that best matches external surface points on one side of the head, with their counterparts on the other side. In our method, the head volume is represented as a re-parameterized surface point cloud, where each location is parameterized by its elevation (latitude), azimuth (longitude), and radius. The search for the best matching surfaces is implemented in a multi-resolution paradigm, and the computation time is significantly decreased. The algorithm was quantitatively evaluated using in both simulated data and in real T1, T2, Flair magnetic resonance patient images. This algorithm is found to be fast (< 10s per MR volume), robust and accurate (< .6 degree of Mean Angular Error), invariant to the acquisition noise, slice thickness, bias field, and pathological asymmetries