Robert A. McLaughlin

Randomized Hough Transform: Improved Ellipse Detection with Comparison

We describe an algorithm for the detection of ellipse shapes in images, using the Randomized Hough Transform. The method is compared with three other Hough-based algorithms. Tests are performed using both noise-free and noisy images, and several real-world images. The algorithm was found to give improvements in accuracy, and a reduction in computation time and the number of false alarms detected. A program allowing the reader to experiment with these algorithms can be found at the WWW address http://ciips.ee.uwa.edu.au/Papers/Journal_Papers/1997/01/Index.html

Intensity-based 2-D - 3-D registration of cerebral angiograms

We propose a new method for aligning three-dimensional (3-D) magnetic resonance angiography (MRA) with 2-D X-ray digital subtraction angiograms (DSA). Our method is developed from our algorithm to register computed tomography volumes to X-ray images based on intensity matching of digitally reconstructed radiographs (DRRs). To make the DSA and DRR more similar, we transform the MRA images to images of the vasculature and set to zero the contralateral side of the MRA to that imaged with DSA. We initialize the search for a match on a user defined circular region of interest. We have tested six similarity measures using both unsegmented MRA and three segmentation variants of the MRA. Registrations were carried out on images of a physical neuro-vascular phantom and images obtained during four neuro-vascular interventions. The most accurate and robust registrations were obtained using the pattern intensity, gradient difference, and gradient correlation similarity measures, when used in conjunction with the most sophisticated MRA segmentations. Using these measures, 95% of the phantom start positions and 82% of the clinical start positions were successfully registered. The lowest root mean square reprojection errors were 1.3 mm (standard deviation 0.6) for the phantom and 1.5 mm (standard deviation 0.9) for the clinical data sets. Finally, we present a novel method for the comparison of similarity measure performance using a technique borrowed from receiver operator characteristic analysis.

In vivo dynamic optical coherence elastography using a ring actuator

We present a novel sample arm arrangement for dynamic optical coherence elastography based on excitation by a ring actuator. The actuator enables coincident excitation and imaging to be performed on a sample, facilitating in vivo operation. Sub-micrometer vibrations in the audio frequency range were coupled to samples that were imaged using optical coherence tomography. The resulting vibration amplitude and microstrain maps are presented for bilayer silicone phantoms and multiple skin sites on a human subject. Contrast based on the differing elastic properties is shown, notably between the epidermis and dermis. The results constitute the first demonstration of a practical means of performing in vivo dynamic optical coherence elastography on a human subject.

Ultrathin side-viewing needle probe for optical coherence tomography

We present the smallest reported side-viewing needle probe for optical coherence tomography (OCT). Design, fabrication, optical characterization, and initial application of a 30-gauge (outer diameter 0.31 mm) needle probe are demonstrated. Extreme miniaturization is achieved by using a simple all-fiber probe design incorporating an angle-polished and reflection-coated fiber-tip beam deflector. When inserted into biological tissue, aqueous interstitial fluids reduce the probes inherent astigmatism ratio to 1.8, resulting in a working distance of 300 μm and a depth-of-field of 550 μm with beam diameters below 30 μm. The needle probe was interfaced with an 840 nm spectral-domain OCT system and the measured sensitivity was shown to be only 7 dB lower than that of a comparable galvo-scanning sample arm configuration. 3D OCT images of lamb lungs were acquired over a depth range of ~600 μm, showing individual alveoli and bronchioles.

Extracting transmission lines from airborne LIDAR data

This letter presents an algorithm to aid in the automatic monitoring of high-voltage transmission lines using airborne light detection and ranging (LIDAR) technology. LIDAR data are first automatically labeled as transmission line, vegetation, or surface. The extracted transmission line data points are then segmented into individual spans using local affine models of the data. The algorithm correctly identified 86.9% of those data points that lay on transmission lines, and extracted 72.1% of the individual transmission line spans.

Strain estimation in phase-sensitive optical coherence elastography

We present a theoretical framework for strain estimation in optical coherence elastography (OCE), based on a statistical analysis of displacement measurements obtained from a mechanically loaded sample. We define strain sensitivity, signal-to-noise ratio and dynamic range, and derive estimates of strain using three methods: finite difference, ordinary least squares and weighted least squares, the latter implemented for the first time in OCE. We compare theoretical predictions with experimental results and demonstrate a ~12 dB improvement in strain sensitivity using weighted least squares compared to finite difference strain estimation and a ~4 dB improvement over ordinary least squares strain estimation. We present strain images (i.e., elastograms) of tissue-mimicking phantoms and excised porcine airway, demonstrating in each case clear contrast based on the sample’s elasticity.

Elastic properties of the central airways in obstructive lung diseases measured using anatomical optical coherence tomography

RATIONALE Our understanding of how airway remodeling affects regional airway elastic properties is limited due to technical difficulties in quantitatively measuring dynamic, in vivo airway dimensions. Such knowledge could help elucidate mechanisms of excessive airway narrowing. OBJECTIVES To use anatomical optical coherence tomography (aOCT) to compare central airway elastic properties in control subjects and those with obstructive lung diseases. METHODS After bronchodilation, airway lumen area (Ai) was measured using aOCT during bronchoscopy in control subjects (n = 10) and those with asthma (n = 16), chronic obstructive pulmonary disease (COPD) (n = 9), and bronchiectasis (n = 8). Ai was measured in each of generations 0 to 5 while airway pressure was increased from -10 to 20 cm H(2)O. Airway compliance (Caw) and specific compliance (sCaw) were derived from the transpulmonary pressure (Pl) versus Ai curves. MEASUREMENTS AND MAIN RESULTS Caw decreased progressively as airway generation increased, but sCaw did not differ appreciably across the generations. In subjects with asthma and bronchiectasis, Caw and sCaw were similar to control subjects and the Pl-Ai curves were left-shifted. No significant differences were observed between control and COPD groups. CONCLUSIONS Proximal airway elastic properties are altered in obstructive lung diseases. Although central airway compliance does not differ from control subjects in asthma, bronchiectasis, or COPD, Ai is lower in asthma and the Pl-Ai relationship is left-shifted in both asthma and bronchiectasis, suggesting that airways are maximally distended at lower inflating pressures. Such changes reflect alteration in the balance between airway wall distensibility and radial traction exerted on airways by surrounding lung parenchyma favoring airway narrowing. Clinical trial registered with Australian New Zealand Clinical Trials Registry (ACTRN12607000624482).

Imaging of Breast Cancer With Optical Coherence Tomography Needle Probes: Feasibility and Initial Results

Optical coherence tomography (OCT) is a high-resolution imaging modality with the potential to provide in situ assessment to distinguish normal from cancerous tissue. However, limited image penetration depth has restricted its utility. This paper demonstrates the feasibility of an OCT needle probe to perform interstitial imaging deep below the tissue surface. The side-facing needle probe comprises miniaturized focusing optics consisting of no-core and GRIN fiber encased within either a 22- or 23-gauge needle. 3-D OCT volumetric data sets were acquired by rotating and retracting the probe during imaging. We present the first published image of a human breast cancer tumor margin, and of human axillary lymph nodes acquired with an OCT needle probe. Through accurate correlation with the histological gold standard, OCT is shown to enable a clear delineation of tumor boundary from surrounding adipose tissue, and identification of microarchitectural features.

Optical coherence micro-elastography: mechanical-contrast imaging of tissue microstructure

We present optical coherence micro-elastography, an improved form of compression optical coherence elastography. We demonstrate the capacity of this technique to produce en face images, closely corresponding with histology, that reveal micro-scale mechanical contrast in human breast and lymph node tissues. We use phase-sensitive, three-dimensional optical coherence tomography (OCT) to probe the nanometer-to-micrometer-scale axial displacements in tissues induced by compressive loading. Optical coherence micro-elastography incorporates common-path interferometry, weighted averaging of the complex OCT signal and weighted least-squares regression. Using three-dimensional phase unwrapping, we have increased the maximum detectable strain eleven-fold over no unwrapping and the minimum detectable strain is 2.6 με. We demonstrate the potential of mechanical over optical contrast for visualizing micro-scale tissue structures in human breast cancer pathology and lymph node morphology.

A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use

Two-dimensional (2-D)-to-three-dimensional (3-D) registration can improve visualization which may aid minimally invasive neurointerventions. Using clinical and phantom studies, two state-of-the-art approaches to rigid registration are compared quantitatively: an intensity-based algorithm using the gradient difference similarity measure; and an iterative closest point (ICP)-based algorithm. The gradient difference approach was found to be more accurate, with an average registration accuracy of 1.7 mm for clinical data, compared to the ICP-based algorithm with an average accuracy of 2.8 mm. In phantom studies, the ICP-based algorithm proved more reliable, but with more complicated clinical data, the gradient difference algorithm was more robust. Average computation time for the ICP-based algorithm was 20 s per registration, compared with 14 min and 50 s for the gradient difference algorithm.