Wesley David Turner

Fast segmentation and high-quality three-dimensional volume mesh creation from medical images for diffuse optical tomography

Abstract. Multimodal approaches that combine near-infrared (NIR) and conventional imaging modalities have been shown to improve optical parameter estimation dramatically and thus represent a prevailing trend in NIR imaging. These approaches typically involve applying anatomical templates from magnetic resonance imaging/computed tomography/ultrasound images to guide the recovery of optical parameters. However, merging these data sets using current technology requires multiple software packages, substantial expertise, significant time-commitment, and often results in unacceptably poor mesh quality for optical image reconstruction, a reality that represents a significant roadblock for translational research of multimodal NIR imaging. This work addresses these challenges directly by introducing automated digital imaging and communications in medicine image stack segmentation and a new one-click three-dimensional mesh generator optimized for multimodal NIR imaging, and combining these capabilities into a single software package (available for free download) with a streamlined workflow. Image processing time and mesh quality benchmarks were examined for four common multimodal NIR use-cases (breast, brain, pancreas, and small animal) and were compared to a commercial image processing package. Applying these tools resulted in a fivefold decrease in image processing time and 62% improvement in minimum mesh quality, in the absence of extra mesh postprocessing. These capabilities represent a significant step toward enabling translational multimodal NIR research for both expert and nonexpert users in an open-source platform.

Model-Based analysis of local shape for lesion detection in CT scans

Thin-slice computer tomography provides high-resolution images that facilitate the diagnosis of early-stage lung cancer. However, the sheer size of the CT volumes introduces variability in radiological readings, driving the need for automated detection systems. The main contribution of this paper is a technique for combining geometric and intensity models with the analysis of local curvature for detecting pulmonary lesions in CT. The local shape at each voxel is represented via the principal curvatures of its associated isosurface without explicitly extracting the isosurface. The comparison of these curvatures to values derived from analytical shape models is then used to label the voxel as belonging to particular anatomical structures, e.g., nodules or vessels. The algorithm was evaluated on 242 CT exams with expert-determined ground truth. The performance of the algorithm is quantified by free-response receiver-operator characteristic curves, as well as by its potential for improvement in radiologist sensitivity.

An open-source toolkit for the volumetric measurement of CT lung lesions

An open source lesion sizing toolkit has been developed with a general architecture for implementing lesion segmentation algorithms and a reference algorithm for segmenting solid and part-solid lesions from lung CT scans. The CT lung lesion segmentation algorithm detects four three-dimensional features corresponding to the lung wall, vasculature, lesion boundary edges, and low density background lung parenchyma. These features form boundaries and propagation zones that guide the evolution of a subsequent level set algorithm. User input is used to determine an initial seed point for the level set and users may also define a region of interest around the lesion. The methods are validated against 18 nodules using CT scans of an anthropomorphic thorax phantom simulating lung anatomy. The scans were acquired under differing scanner parameters to characterize algorithm behavior under varying acquisition protocols. We also validated repeatability using six clinical cases in which the patient was rescanned on the same day (zero volume change). The source code, data sets, and a running application are all provided under an unrestrictive license to encourage reproducibility and foster scientific exchange.

Part-Based local shape models for colon polyp detection

This paper presents a model-based technique for lesion detection in colon CT scans that uses analytical shape models to map the local shape curvature at individual voxels to anatomical labels. Local intensity profiles and curvature information have been previously used for discriminating between simple geometric shapes such as spherical and cylindrical structures. This paper introduces novel analytical shape models for colon-specific anatomy, viz. folds and polyps, built by combining parts with simpler geometric shapes. The models better approximate the actual shapes of relevant anatomical structures while allowing the application of model-based analysis on the simpler model parts. All parameters are derived from the analytical models, resulting in a simple voxel labeling scheme for classifying individual voxels in a CT volume. The algorithms performance is evaluated against expert-determined ground truth on a database of 42 scans and performance is quantified by free-response receiver-operator curves.

An automated approach and virtual environment for generating maintenance instructions

Maintenance of complex machinery such as aircraft engines requires reliable and accurate documentation, including illustrated parts catalogs (IPCs), exploded views, and technical manuals describing how to remove, inspect, repair and install parts. For new designs, there are often time constraints for getting a new engine to the field, and the available documentation must go with it. Authoring technical manuals is a complex process involving technical writers, engineers, as well as domain experts (mechanics and designers). Often, several revisions are required before a manual has correct IPC figures and maintenance instructions. Compounding this problem is that technical writers often perform tasks better suited for computers, leading to increased costs and error.In this demonstration, we describe a new framework to generate maintenance instructions from solid models (Computer Aided Design/CAD data) and then validate these instructions in a haptics-enabled virtual environment. Our approach utilizes natural language processing techniques to generate a presentation-independent logical form, which can be transformed for display within the virtual environment. During the development of the system, task analyses, human models, usability studies, and domain experts were used to gain insights. The end result is a more integrated and human-centered process for developing technical manuals, providing higher quality documents with less cost.

Automated coronary CT angiography plaque-lumen segmentation

We are investigating the feasibility of a computer-aided detection (CAD) system to assist radiologists in diagnosing coronary artery disease in ECG gated cardiac multi-detector CT scans having calcified plaque. Coronary artery stenosis analysis is challenging if calcified plaque or the iodinated blood pool hides viable lumen. The research described herein provides an improved presentation to the radiologist by removing obscuring calcified plaque and blood pool. The algorithm derives a Gaussian estimate of the point spread function (PSF) of the scanner responsible for plaque blooming by fitting measured CTA image profiles. An initial estimate of the extent of calcified plaque is obtained from the image evidence using a simple threshold. The Gaussian PSF estimate is then convolved with the initial plaque estimate to obtain an estimate of the extent of the blooming artifact and this plaque blooming image is subtracted from the CT image to obtain an image largely free of obscuring plaque. In a separate step, the obscuring blood pool is suppressed using morphological operations and adaptive region growing. After processing by our algorithm, we are able to project the segmented plaque-free lumen to form synthetic angiograms free from obstruction. We can also analyze the coronary arteries with vessel tracking and centerline extraction to produce cross sectional images for measuring lumen stenosis. As an additional aid to radiologists, we also produce plots of calcified plaque and lumen cross-sectional area along selected blood vessels. The method was validated using digital phantoms and actual patient data, including in one case, a validation against the results of a catheter angiogram.

Using Computer Vision to Map Laser Ultrasound Onto CAD Geometries

Wide area imaging devices offer many speed and flexibility advantages to NDE applications. They can be reconfigured quickly to accommodate a variety of part geometries and sizes and can be deployed without precise fixturing for the sensor or the part. When the part to be inspected is large or complicated (with many bends); applications use several sensors or move a single sensor to multiple viewpoints to complete an inspection. An operator must then review several images for a single part, spatially relate indications across disparate images, and assume the collection of images completely covers the part. We describe a system that uses laser‐ultrasound as a wide area, imaging device. The system also uses a structured light range camera — typically used to measure shape — to locate the part in the work cell. We describe how camera calibration, photogrammetry, triangulation, and registration techniques are used to define coordinate frames that allow us to relate the data from the laser‐ultrasound imaging de...

Multilevel preconditioned QMR methods for unstructured mesh computation

We present a variant of the Quasi-Minimal Residual (QMR) algorithm of Freund and Nachtigal with a preconditioner based on the Algebraic Multilevel (AMLI) algorithm of Axelsson and Vassilevski. This combination provides an effective solution method for indefinite algebraic systems and is tested by application to finite element discretizations of the Helmholtz equation. The implementation is applicable with both h- and p-refinements, and easily extends to a parallel environment.

Tracking flow of leukocytes in blood for drug analysis

Modern microscopy techniques allow imaging of circulating blood components under vascular flow conditions. The resulting video sequences provide unique insights into the behavior of blood cells within the vasculature and can be used as a method to monitor and quantitate the recruitment of inflammatory cells at sites of vascular injury/ inflammation and potentially serve as a pharmacodynamic biomarker, helping screen new therapies and individualize dose and combinations of drugs. However, manual analysis of these video sequences is intractable, requiring hours per 400 second video clip. In this paper, we present an automated technique to analyze the behavior and recruitment of human leukocytes in whole blood under physiological conditions of shear through a simple multi-channel fluorescence microscope in real-time. This technique detects and tracks the recruitment of leukocytes to a bioactive surface coated on a flow chamber. Rolling cells (cells which partially bind to the bioactive matrix) are detected counted, and have their velocity measured and graphed. The challenges here include: high cell density, appearance similarity, and low (1Hz) frame rate. Our approach performs frame differencing based motion segmentation, track initialization and online tracking of individual leukocytes.

A Multi-Institutional Perspective on H/FOSS Projects in the Computing Curriculum

Many computer science programs have capstone experiences or project courses that allow students to integrate knowledge from the full breadth of their major. Such capstone projects may be student-designed, instructor-designed, designed in conjunction with outside companies, or integrated with ongoing free and open source (FOSS) projects. The literature shows that the FOSS approach has attracted a great deal of interest, in particular when implemented with projects that have humanitarian goals (HFOSS). In this article, we describe five unique models from five distinct types of institutions for incorporating sustained FOSS or HFOSS (alternatively H/FOSS) project work into capstone experiences or courses. The goal is to provide instructors wishing to integrate open source experiences into their curriculum with additional perspectives and resources to help in adapting this approach to the specific needs and goals of their institution and students. All of the models presented are based on sustained engagement with H/FOSS projects that last at least one semester and often more. Each model is described in terms of its characteristics and how it fits the needs of the institution using the model. Assessment of each model is also presented. We then discuss the themes that are common across the models, such as project selection, team formation, mentoring, and student assessment. We examine the choices made by each model, as well as the challenges faced. We end with a discussion how the models have leveraged institutional initiatives and collaborations with outside organizations to address some of the challenges associated with these projects.