William W. Lau

Stereo-Based Endoscopic Tracking of Cardiac Surface Deformation

We propose an image-based motion tracking algorithm that can be used with stereo endoscopic and microscope systems. The tracking problem is considered to be a time-varying optimization of a parametric function describing the disparity map. This algorithm could be used as part of a virtual stabilization system that can be employed to compensate residual motion of the heart during robot-assisted off-pump coronary artery bypass surgery (CABG). To test the appropriateness of our methods for this application, we processed an image sequence of a beating pig heart obtained by the stereo endoscope used in the da Vinci robotic surgery system. The tracking algorithm was able to detect the beating of the heart itself as well as the respiration of the lungs.

Navigating inner space: 3-D assistance for minimally invasive surgery

Abstract Since its inception about three decades ago, modern minimally invasive surgery has made huge advances in both technique and technology. However, the minimally invasive surgeon is still faced with daunting challenges in terms of visualization and hand-eye coordination. At the Center for Computer Integrated Surgical Systems and Technology (CISST) we have been developing a set of techniques for assisting surgeons in navigating and manipulating the three-dimensional space within the human body. In order to develop such systems, a variety of challenging visual tracking, reconstruction and registration problems must be solved. In addition, this information must be tied to methods for assistance that improve surgical accuracy and reliability but allow the surgeon to retain ultimate control of the procedure and do not prolong time in the operating room. In this article, we present two problem areas, eye microsurgery and thoracic minimally invasive surgery, where computational vision can play a role. We then describe methods we have developed to process video images for relevant geometric information, and related control algorithms for providing interactive assistance. Finally, we present results from implemented systems.

Real-Time endoscopic mosaicking

With the advancement of minimally invasive techniques for surgical and diagnostic procedures, there is a growing need for the development of methods for improved visualization of internal body structures. Video mosaicking is one method for doing this. This approach provides a broader field of view of the scene by stitching together images in a video sequence. Of particular importance is the need for online processing to provide real-time feedback and visualization for image-guided surgery and diagnosis. We propose a method for online video mosaicking applied to endoscopic imagery, with examples in microscopic retinal imaging and catadioptric endometrial imaging.

Real-time 3D Surface Tracking and Its Applications

We present a general technique for directly estimating and tracking surfaces from a stream of rectified stereo pairs in real-time. These techniques are based on the iterative updating of surface representations directly from image information and use no disparity search except during initialization. We perform the tracking through an iteratively re-weighted least squares minimization wherein a mask is incorporated to increase robustness to occlusion. The algorithms are formulated for a general family of linear in parameters surface models and discussed for the cases of planar surfaces and tensor product surfaces. These algorithms have been implemented on standard hardware and run at or near frame rate, with accuracy on the order of 1/20 of a pixel. We discuss applications of the technique including mobile robot localization, general deforming surface tracking, and biometry of biological surfaces.

Spatiotemporal characteristics of low-frequency functional activation measured by laser speckle imaging

Changes in neuronal activity have been shown to be accompanied by alteration in regional cerebral blood flow . In the present study, laser speckle imaging (LSI) was employed to measure stimulus-evoked neuronal activities in rat barrel cortex. The spatiotemporal characteristics of hemodynamic response to mechanical stimuli from 1 to 3 Hz were examined. Time to peak amplitude reduced from 4.5 to 3.5 s with increasing frequencies. Spatially, the response was confined to a small circular region at the beginning and then spread out asymmetrically to the surrounding regions. The maximal area of activation ranged from 2.2 to 3.5 mm/sup 2/, while the time to reach maximal area occurred between 5.5 and 6 s. Moreover, there was a high correlation between LSI and laser-Doppler flowmetry in terms of peak response magnitude and the time to reach peak. These two values were linearly dependent on stimulus frequency whereas area of activation and time to maximal area appeared to be independent of this parameter. LSIs high sensitivity, low cost of the equipment, and size and complexity make this a suitable technique for fundamental neurophysiological investigations.

Expanding the Immunology Toolbox: Embracing Public-Data Reuse and Crowdsourcing

New technologies have been propelling dramatic increases in the volume and diversity of large-scale public data, which can potentially be reused to answer questions beyond those originally envisioned. However, this often requires computational and statistical skills beyond the reach of most bench scientists. The development of educational and accessible computational tools is thus critical, as are crowdsourcing efforts that utilize the communitys expertise to curate public data for hypothesis generation and testing. Here we review the history of public-data reuse and argue for greater incorporation of computational and statistical sciences into the biomedical education curriculum and the development of biologist-friendly crowdsourcing tools. Finally, we provide a resource list for the reuse of public data and highlight an illustrative crowdsourcing exercise to explore public gene-expression data of human autoimmune diseases and corresponding mouse models. Through education, tool development, and community engagement, immunologists will be poised to transform public data into biological insights.

Four-wavelength near-infrared imaging of abdominal aorta blood flow under surgical occlusion

This paper presents a four-wavelength near-infrared imaging system that can assist surgeons with intraoperative monitoring and imaging of blood flow of the vessel being occluded. The algorithm for this system, based on the Beer-Lambert law, calculates the relative concentrations of deoxyhemoglobin, oxyhemoglobin and water, which are the major NIR absorbers in tissues. Regional blood volume and oxygen saturation can be determined from these measurements. This proof-of-concept study investigated the utility of the algorithm on detecting rat infrarenal abdominal aortic blood flow subjected to various degrees of occlusion. The images provided a good visualization of the aorta because of the high concentration of oxyhemoglobin in the blood stream. The imager was able to detect when blood flow was completely stopped. Average intensity values of the blood volume images correlated well with the laser Doppler recordings.

Towards Personalized Medicine: An Improved De Novo Assembly Procedure for Early Detection of Drug Resistant HIV Minor Quasispecies in Patient Samples

The third-generation sequencing technology, PacBio, has shown an ability to sequence the HIV virus amplicons in their full length. The long read of PaBio offers a distinct advantage to comprehensively understand the virus evolution complexity at quasispecies level (i.e. maintaining linkage information of variants) comparing to the short reads from Illumina shotgun sequencing. However, due to the highnoise nature of the PacBio reads, it is still a challenge to build accurate contigs at high sensitivity. Most of previously developed NGS assembly tools work with the assumption that the input reads are fairly accurate, which is largely true for the data derived from Sanger or Illumina technologies. When applying these tools on PacBio high-noise reads, they are largely driven by noise rather than true signal eventually leading to poor results in most cases. In this study, we propose the de novo assembly procedure, which comprises a positivefocused strategy, and linkage-frequency noise reduction so that it is more suitable for PacBio high-noise reads. We further tested the unique de novo assembly procedure on HIV PacBio benchmark data and clinical samples, which accurately assembled dominant and minor populations of HIV quasispecies as expected. The improved de novo assembly procedure shows potential ability to promote PacBio technology in the field of HIV drug-resistance clinical detection, as well as in broad HIV phylogenetic studies.

Humoral Fingerprinting of Immune Responses: ‘Super-Resolution’, High-Dimensional Serology

In a recent study, Chung et al. report the development of a high-dimensional approach to assess humoral responses to immune perturbation that goes beyond antibody neutralization and titers. This approach enables the identification of potentially novel correlates and mechanisms of protective immunity to HIV vaccination, thus offering a glimpse of how dense phenotyping of serological responses coupled with bioinformatics analysis could lead to much-sought-after markers of protective vaccination responses.

Three-Dimensional Spot Detection in Ratiometric Fluorescence Imaging For Measurement of Subcellular Organelles

Lysosomes are subcellular organelles playing a vital role in the endocytosis process of the cell. Lysosomal acidity is an important factor in assuring proper functioning of the enzymes within the organelle, and can be assessed by labeling the lysosomes with pH-sensitive fluorescence probes. To enhance our understanding of the acidification mechanisms, the goal of this work is to develop a method that can accurately detect and characterize the acidity of each lysosome captured in ratiometric fluorescence images. We present an algorithm that utilizes the h-dome transformation and reconciles spots detected independently from two wavelength channels. We evaluated our algorithm using simulated images for which the exact locations were known. The h-dome algorithm achieved an f-score as high as 0.890. We also computed the fluorescence ratios from lysosomes in live HeLa cell images with known lysosomal pHs. Using leave-one-out cross-validation, we demonstrated that the new algorithm was able to achieve much better pH prediction accuracy than the conventional method.