Search

The purpose of this paper is to recover dense correspondence between non-rigid shapes for anatomical objects, which is a key element of disease diagnosis and analysis. We proposed a shape matching framework based on Markov random fields to obtain non-rigid correspondence. We constructed an energy function by summing up two terms where one was a unary term and the other was a binary term. By using this formulation, shape matching was represented as an energy function minimisation problem. Loopy belief propagation (LBP) was then used to minimize the energy function. We adopted a new sparse update technique for LBP update to increase computational efficiency. At the same time, we also proposed to use a novel clamping technique, an expectation-maximization (EM) like approach, to enhance matching accuracy. Experiments with the hippocampal data from OASIS and PATH showed that the sparse update was 160 times faster than standard BP. By iteratively running the EM-like clamping procedure, we were able to obtain high quality non-rigid correspondence results to achieve 97% matching rate between two hippocampi. Our shape matching based approach overcomes the flip problem of first-order ellipsoid and does not assume pre-alignment unlike iterative closest point.

One important index to assess left ventricular diastolic function is the quantitative measurement of atrioventricular junction (AVJ) motion in one cardiac cycle including systole and diastole. The best way to perform the measurement is to use a software tool that can conduct AVJ motion tracking from cine cardiovascular magnetic resonance (CMR) images. In this paper, a software tool for this purpose is presented by using the insight segmentation and registration toolkit (ITK), the visualization toolkit (VTK), and Qt. We propose a surface area-based tracking approach in the software tool. In the tracking approach to obtain the surface area swept by six points being tracked, we manually select six points from four-, three- and two-chamber views of CMR images. After that, we reconstruct the 3-D coordinates of the six points from image acquisition parameters extracted from DICOM files. We perform interpolation by using parametric cubic curve fitting techniques. From the curve fitting results, we finally obtain the surface areas for all time points in one cardiac cycle. The software tool has been successfully implemented. The functionality include single point-based tracking, surface area-based tracking by using 6 tracked points, generation of displacement, sweep surface area and velocity, and generation of tracking movies. From the software engineering practice, it is concluded that ITK, VTK, and Qt are very handy software systems to implement automatic image analysis functions for CMR images, such as quantitative measure of motion by visual tracking. The software tool provides a convenient and efficient way to measure AVJ motion and extends the scope of methods for ventricular function assessment., We use sweep surface area (SSA), defined by 6 tracked points in 4-, 3- and 2-chamber views of cine cardiovascular magnetic resonance (CMR) images with 2 points in each view in Atrioventricular Junction (AVJ) region, to realize surface area based tracking for left ventricular (LV) function assessment. It is demonstrated that the surface area based tracking presented in this paper gives better performance than the single point based tracking in our previous paper in terms of reproducibility.

We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell segmentation and tracking algorithms. With 21 participating algorithms and a data repository consisting of 13 data sets from various microscopy modalities, the challenge displays today's state-of-the-art methodology in the field. We analyzed the challenge results using performance measures for segmentation and tracking that rank all participating methods. We also analyzed the performance of all of the algorithms in terms of biological measures and practical usability. Although some methods scored high in all technical aspects, none obtained fully correct solutions. We found that methods that either take prior information into account using learning strategies or analyze cells in a global spatiotemporal video context performed better than other methods under the segmentation and tracking scenarios included in the challenge.

The quantitative measurement of the Atrioventricular Junction (AVJ) motion is an important index for ventricular functions of one cardiac cycle including systole and diastole. In this paper, a software tool that can conduct AVJ motion tracking from cardiovascular magnetic resonance (CMR) images is presented by using Insight Segmentation and Registration Toolkit (ITK), The Visualization Toolkit (VTK) and Qt. The software tool is written in C++ by using Visual Studio Community 2013 integrated development environment (IDE) containing both an editor and a Microsoft complier. The software package has been successfully implemented. From the software engineering practice, it is concluded that ITK, VTK, and Qt are very handy software systems to implement automatic image analysis functions for CMR images such as quantitative measure of motion by visual tracking.

A dense point-based registration is an ideal starting point for detailed comparison between two neuroanatomical objects. This paper presents a new algorithm for global dense point-based registration between anatomical objects without assumptions about their shape. We represent mesh models of the surfaces of two similar 3D anatomical objects using a Markov Random Field and seek correspondence pairs between points in each shape. However, for densely sampled objects the set of possible point by point correspondences is very large. We solve the global non-rigid matching problem between the two objects in an efficient manner by applying loopy belief propagation. Typically loopy belief propagation is of order m^3 for each iteration, where m is the number of nodes in a mesh. By avoiding computation of probabilities of configurations that cannot occur in practice, we reduce this to order m^2. We demonstrate the method and its performance by registering hippocampi from a population of individuals aged 60-69. We find a corresponding rigid registration, and compare the results to a state-of-the-art technique and show comparable accuracy. Our method provides a global registration without prior information about alignment, and handles arbitrary shapes of spherical topology.

Medical imaging research and clinical applications usually require combination and integration of various techniques ranging from image processing and analysis to realistic visualization to user-friendly interaction. Researchers with different backgrounds coming from diverse areas have been using numerous types of hardware, software, and environments to obtain their results. We also observe that students often build their tools from scratch resulting in redundant work. A generic and flexible medical imaging and visualization toolkit would be helpful in medical research and educational institutes to reduce redundant development work and hence increase research efficiency. This paper presents our experience in developing a Medical Imaging and Visualization Toolkit (BIL-kit) that is a set of comprehensive libraries as well as a number of interactive tools. The BIL-kit covers a wide range of fundamental functions from image conversion and transformation, image segmentation, and analysis to geometric model generation and manipulation, all the way up to 3D visualization and interactive simulation. The toolkit design and implementation emphasize the reusability and flexibility. BIL-kit is implemented in the Java language so that it works in hybrid and dynamic research and educational environments. This also allows the toolkit to extend its usage for the development of Web-based applications. Several BIL-kit-based tools and applications are presented including image converter, image processor, general anatomy model simulator, vascular modeling environment, and volume viewer. BIL-kit is a suitable platform for researchers and students to develop visualization and simulation prototypes, and it can also be used for the development of clinical applications.

In this paper, scheduling problems, including description, solving, and rescheduling, are presented in detail. The scheduling flexibility is an important factor to affect the system flexibility.