Bipolar disorder is a mental illness with lifetime prevalence of about 1%. Previous genetic studies have identified multiple chromosomal linkage regions and candidate genes that might be associated with bipolar disorder. The present study aimed to identify potential susceptibility variants for bipolar disorder using 6 related case samples from a four-generation family. A combination of exome sequencing and linkage analysis was performed to identify potential susceptibility variants for bipolar disorder. Our study identified a list of five potential candidate genes for bipolar disorder. Among these five genes, GRID1(Glutamate Receptor Delta-1 Subunit), which was previously reported to be associated with several psychiatric disorders and brain related traits, is particularly interesting. Variants with functional significance in this gene were identified from two cousins in our bipolar disorder pedigree. Our findings suggest a potential role for these genes and the related rare variants in the onset and development of bipolar disorder in this one family. Additional research is needed to replicate these findings and evaluate their patho-biological significance.

Superpixel algorithms have proven to be a useful initial step for segmentation and subsequent processing of images, reducing computational complexity by replacing the use of expensive per-pixel primitives with a higher-level abstraction, superpixels. They have been successfully applied both in the context of traditional image analysis and deep learning based approaches. In this work, we present a general- ized implementation of the simple linear iterative clustering (SLIC) superpixel algorithm that has been generalized for n-dimensional scalar and multi-channel images. Additionally, the standard iterative im- plementation is replaced by a parallel, multi-threaded one. We describe the implementation details and analyze its scalability using a strong scaling formulation. Quantitative evaluation is performed using a 3D image, the Visible Human cryosection dataset, and a 2D image from the same dataset. Results show good scalability with runtime gains even when using a large number of threads that exceeds the physical number of available cores (hyperthreading).

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The National Institutes of Health (NIH) has launched the NIH 3D Print Exchange, an online portal for discovering and creating bioscientifically relevant 3D models suitable for 3D printing, to provide both researchers and educators with a trusted source to discover accurate and informative models. There are a number of online resources for 3D prints, but there is a paucity of scientific models, and the expertise required to generate and validate such models remains a barrier. The NIH 3D Print Exchange fills this gap by providing novel, web-based tools that empower users with the ability to create ready-to-print 3D files from molecular structure data, microscopy image stacks, and computed tomography scan data. The NIH 3D Print Exchange facilitates open data sharing in a community-driven environment, and also includes various interactive features, as well as information and tutorials on 3D modeling software. As the first government-sponsored website dedicated to 3D printing, the NIH 3D Print Exchange is an important step forward to bringing 3D printing to the mainstream for scientific research and education.

SimpleITK is a new interface to the Insight Segmentation and Registration Toolkit (ITK) designed to facilitate rapid prototyping, education and scientific activities via high level programming languages. ITK is a templated C++ library of image processing algorithms and frameworks for biomedical and other applications, and it was designed to be generic, flexible and extensible. Initially, ITK provided a direct wrapping interface to languages such as Python and Tcl through the WrapITK system. Unlike WrapITK, which exposed ITK's complex templated interface, SimpleITK was designed to provide an easy to use and simplified interface to ITK's algorithms. It includes procedural methods, hides ITK's demand driven pipeline, and provides a template-less layer. Also SimpleITK provides practical conveniences such as binary distribution packages and overloaded operators. Our user-friendly design goals dictated a departure from the direct interface wrapping approach of WrapITK, toward a new facade class structure that only exposes the required functionality, hiding ITK's extensive template use. Internally SimpleITK utilizes a manual description of each filter with code-generation and advanced C++ meta-programming to provide the higher-level interface, bringing the capabilities of ITK to a wider audience. SimpleITK is licensed as open source software library under the Apache License Version 2.0 and more information about downloading it can be found at http://www.simpleitk.org.

We present a new filter for the Insight Toolkit (ITK) for reducing the resolution of an image by an integer factor while averaging called BinShrink. This filter provides a new level of performance to ITK for reducing resolution and noise present in an image. The filter supports streaming, multi-threading and most of ITK’s pixel types including scalars, Vectors, SymmetricSecondRankTensors, and RGBPixels. The filter has been optimized to efficiently access the input image thereby greatly increasing performance over conventional methods.

More than 15 years ago, the Visible Human Project (VHP) announced the most detailed study of human anatomy ever attempted. The study employed emerging technology in digital photography and cryosectioning, a destructive imaging technique that achieves pixel resolutions on the order of 300 microns across subjects nearly 2 meters long. The resulting datasets exceeded 17 Gbytes and represented a landmark in the medical sciences. Today, the High Performance Computing and Communications Office and the Audiovisual Program Development Branch of the US National Library of Medicine and the Laboratory of Cell Biology at the US National Cancer Institute are teaming up to investigate biomedical sciences at nanometer scales using ion-abrasion scanning electron microscopy (IA-SEM). IA-SEM is an emerging technology for 3D imaging of whole cells and tissues at resolutions in the 10-nm range. Despite the difference in subject and scale across the subject matter, the methods for analyzing and modeling them are remarkably similar. They are derived from image-processing, computer vision, and computer graphics techniques. Our process reduces large data to a manageable computational model suitable for quantitative analysis while promoting abstract concepts of shape, structure, and function. Moreover, we are employing medical illustration, visualization, and rapid prototyping to inform and inspire the biomedical sciences. By combining graphics and biology, we are imaging biologically relevant objects at the nano and macro scales to improve public health through research.

This paper describes our contribution of three new classes to the Insight Toolkit community. We present a new ImageIO base class for streaming image file, along with two derived ImageIO classes for the VTK and the MRC file formats.

Quantitative analysis of breast morphometry is critical to breast plastic surgery. Recently, three-dimensional (3D) photography has emerged as a strong new alternative for breast morphometry analysis in comparison to other existing techniques. 3D photography enables the capture of the entire breast surface topology virtually in a single snapshot and without any direct contact with the patient, thus causing minimal discomfort. In this paper, we present a set of computational tools for the quantitative analysis of two key morphological properties of the breast that are of interest to breast plastic surgery based on 3D scans, namely breast shape and volume. The breast shape is modeled using a compact geometric model capable of capturing the global shape of the breast with very few parameters. Specifically, the shape model is deduced by applying a set of five global deformations to a geometric primitive. These deformations, defined using very intuitive parameters, closely model the key shape variables that surgeons inherently use to describe the overall shape of the breast. Patient-specific parameters of the breast shape model are automatically recovered by fitting a generic breast shape model to the 3D scan of the patient's breast using a physics-based deformable model framework. The mean error of fit between the automatically fitted shape model and the actual breast surface for 12 subjects varied between 0.9 and 2.6 mm. These results are very encouraging considering the fact that only 17 parameters are used to determine the shape of the breast. The breast volume is estimated automatically by first localizing the breast on a 3D scan of the patient's torso and then computing the volume enclosed between an interpolated breast-less torso surface and the actual breast. The volume estimated by the proposed method was found to be within the intra-operator variability among five segmentation trials performed manually by an expert on 3D torso scans of three subjects.

The existing CMake and CTest environment provides an excellent platform for execution and submission of software quality tests. However, there is little support or aid for regression type tests provided to lessen the burden of writing tests and verifying the results. We propose an additional facility to compare measurements generated by a software quality test to a based-line result. Our approach enables the ability to use multiple images as measurements, along with integer, floating point and string values for regression tests. We describe a new testing class framework which provides the functionality of reading, writing, comparing and differentiating named measurements.

We present a novel hierarchical spatial partitioning method for creating interpolating implicit surfaces using compactly supported radial basis functions (RBFs) from scattered surface data. From this hierarchy of functions we can create a range of models from coarse to fine, where a coarse model approximates and a fine model interpolates. Furthermore, our method elegantly handles irregularly sampled data and hole filling because of its multiresolutional approach. Like related methods, we combine neighboring patches without surface discontinuities by overlapping their embedding functions. However, unlike partition-of-unity approaches we do not require an additional explicit blending function to combine patches. Rather, we take advantage of the compact extent of the basis functions to directly solve for each patch's embedding function in a way that does not cause error in neighboring patches. Avoiding overlap error is accomplished by adding phantom constraints to each patch at locations where a neighboring patch has regular constraints within the area of overlap (the function's radius of support). Phantom constraints are also used to ensure the correct results between different levels of the hierarchy. This approach leads to efficient evaluation because we can combine the relevant embedding functions at each point through simple summation. We demonstrate our method on the Thai statue from the Stanford 3D Scanning Repository. Using hierarchical compactly supported RBFs we interpolate all 5 million vertices of the model.

We set out to explore new domains of computer graphics through uncommon media, pushing the bounds of non-photorealistic rendering (NPR). We use computer graphics NPR methods to move beyond the common pen-and-ink or impressionist oil painting styles, and we have implemented computer generated Blackwork, a decorative art of embroidery originating in Elizabethan times to add detail to clothing. The basic techniques of blackwork were later used as an illustrative form, revived in mid 20th century. We adopt these methods, to computer graphics and show how iconic objects such as the Utah teapot (and the less well known teacup) can be rendered anew using vintage media. We add a very uncommon twist, animating embroidery, a media that does not lend itself to moving images, perhaps for the first time. Using PLAWARe, our layered software architecture for NPR, we implemented a system to place artistic embroidery primitives according the principles of blackwork, an embroidery style popular in the sixteenth and seventeenth centuries. A 20-century revival of blackwork generates variation in tones, contrasting lights and darks, through elaborate fill patterns. This more modern blackwork resembles that of a pen-and-ink drawings. These techniques are designed specifically with embroidered primitives in mind. They are not simply rendered images, converted to rastered TIFF files, then digitized in the same fashion as trademarked logos for promotional garments. We instead derive the tone of each region of the scene and place individual stitches using directives for automated embroidery tools. In this direct process, we generate no output image files, but rather a control file for the stitching machine itself. Our modern interpretation renders polygonal objects using computer graphics techniques, and using computer controlled embroidery machines, translates them to embroidered panels. We choose the venerable Utah Teapot as our subject for a still life, connecting a tradition in the field of computer graphics to this centuries-old art form. Beyond the casting of an old art form into computer graphics, we employ the power of computer control to animate what is traditionally a hand craft. Our exhibit is a proposed installation, a zoetrope, a simple mechanical animation tool where we expect to mount twelve 9-inch embroidered panels around the inside of a slotted, rotating 3-foot diameter cylinder creating a moving animation loop of blackwork embroidered renderings. The use of real panels, rather than photographs is considered essential to convey the tangible aspects of this technique.

Interaction with medical volume data has often been difficult, due to the large memory and computational power required. By taking advantage of current high-end graphics hardware, we have developed a volumetric virtual environment that provides the ability to help people interact with the volumetric Visible Human data set. The application enables the user to explore the interior of a virtual human body in a natural and intuitive way

Interaction with volume data has often been difficult due to the large memory and processing power required. By taking advantage of current high-end graphics hardware, a volumetric virtual environment has been developed, which allows a user to interact with a volumetric visible human data set. The application enables the user to explore the interior of a virtual human body in a natural and intuitive way.

This paper introduces Distributed PaulingWorld, a Distributed Virtual Environment application that supports collaborative visualization of molecular structures among multiple users within the same virtual environment. All the participants in the virtual environment have the same level of interaction in the application. In the application, a virtual menu that is attached to the left hand of the user is used to manipulate the molecule and the environment. The user that has the virtual menu has total control of the environment and the viewpoint of the users in the virtual environment. However, the virtual menu can also be transfer to another user in the virtual environment. Only the user that has the menu can chose to transfer the menu. At that point, the other user, upon receiving the virtual menu, will have the capability to manipulate the molecule and the virtual environment. Users are represented by avatars to indicate their location within the virtual environment.

In this paper, we present the modeling and estimation aspects of a virtual reality system for plastic and reconstructive breast surgery. Our system has two modes, a model creation mode and a model fitting mode. The model creation mode allows a surgeon to interactively adjust the shape of a virtual breast by varying key shape variables, analogous to the aesthetic and structural elements surgeons inherently vary manually during breast reconstruction. Our contribution is a set of global deformations with very intuitive parameters that a surgeon can apply to a generic geometric primitive in order to model the breast of his/her patient for pre-operative planning purposes and for communicating this plan to the patient. The model fitting mode allows the system to automatically fit a generic deformable model to patient specific three-dimensional breast surface measurements using a physically-based framework. We have tested the accuracy of our technique using both synthetic and real input data with very encouraging results.

Polar Ozone and Aerosol Measurement (POAM) III, a follow-on to the successful POAM II, is a spaceborne experiment designed to measure the vertical profiles of ozone, water vapor, nitrogen dioxide, and aerosol extinction in the polar stratosphere and upper troposphere with a vertical resolution of 1–2 km. Measurements are made by the solar occultation technique. POAM III, now in polar orbit aboard the SPOT 4 satellite, is providing data on north- and south-polar ozone phenomena, including the south-polar ozone hole, and on the spatial and temporal variability of stratospheric aerosols, polar stratospheric clouds, and polar mesospheric clouds. Differences between the POAM III and POAM II instruments are described. First validations of POAM III data products by comparison with Halogen Occultation Experiment and ozonesonde data are presented.