Robust phase unwrapping for phase images in Fourier domain Doppler optical coherence tomography.

Interferometric temperature measurement around an isolated boiling bubble was conducted for studying heat transfer from liquid phase to the bubble. Finite fringe interferogram was captured with Mach-Zehnder type interferometer and a high-speed camera. Brightness distribution in the interferogram was converted to series wrapped phase image and axisymmetric differential temperature image through wrapped phase image, differential phase image, unwrapped phase image, and differential refractive index image by the Hilbert transform and Abel inversion. The resulted differential temperature image shows that the superheated liquid layer on the heating surface is lifted up and stretched by the growing bubble, and that hot liquid flow is accompanied by departed bubble.

New method of multi-extremal optimization has been developed - a network programming method, which is based on the possibility to represent a complex function as a superposition of simpler functions. The paper deals with network (dichotomous) programming method and its application for solving multi-extremal and discrete optimization problems in Project Management. The main goal of the paper is to develop a new approach to solving knapsack problem and to solve a number of optimization problems of project building management. The optimal structure of the dichotomous representation is determined. On the basis dichotomous programming method new algorithm to solve a optimization problem is proposed

Tissue engineering, rapidly developing branch of bioscience, is widely adopted for the purposes of the tissue growing using the substrate materials. Three-dimensional porous scaffolds possess a great opportunity for the directional growth of the cells and for the supplying them with nutrients. However, the complex porous structure of the scaffolds creates difficulties for the measurements and control of nutrients flow. We applied optical coherence tomography (OCT) for imaging of the scaffold structure. We also investigated the possibility of using Doppler OCT to monitor the flow velocity distribution within the scaffold. The average scaffold's pore diameter has been estimated using electron microscopy. We show that with Doppler OCT it is possible to monitor complex micro-flow and estimate the shear stress (i.e. enhancing factor of cell growing) acting on the cells within the scaffold and to find the optimal input flow rate, consequently.

Three-dimensional Vascular Imaging of Proliferative Diabetic Retinopathy by Doppler Optical Coherence Tomography

The rupture of an intracranial aneurysm can cause spontaneous subarachnoid hemorrhage and result in sudden death. A large portion of intracranial aneurysms occurs near the center of the head, at the skull base, which poses significant technical challenge to neurosurgeons due to limited accessibility. The utilization of angiography is prominent during the treatment of intracranial aneurysms. However, malapposition of stent or incomplete packing of the intracranial aneurysm can be difficult to assess with angiography, and could lead to severe postoperative complications. As a result, angiography may not be sufficient in determining the risk of rupture as the compensatory mechanisms are known to occur at the microstructural level due to the local hemodynamics in the arterial lumen, as well as in evaluating the intraoperative treatment. In this work, we describe a method for assessing intracranial aneurysm through the evaluation of blood flow within the lumen and morphological structures of the arterial wall with optical coherence tomography (OCT). Sterile intravascular fiber-optic catheters can be introduced in the artery to detect blood flow. Prior to this work, limited investigations of catheter based Doppler OCT (DOCT) were reported. A novel signal processing technique was developed to further reduce the effect of Doppler noise within a catheter based DOCT system. This technique consisted of splitting the interferogram of an OCT signal prior to estimating the Doppler shift. This split spectrum DOCT (ssDOCT) method was evaluated through flow models and porcine models, as well as through the correlation between ssDOCT algorithm and computational fluid dynamic (CFD) models. It was observed that ssDOCT provided improved Doppler artefact suppression over the conventional DOCT technique. ssDOCT also provided the ability to estimate lower velocities within the DOCT image to measure the hemodynamic patterns around stent struts in both the internal carotid and patient specific flow phantoms. An OCT imaging study was also conducted consisting of surgically resected human intracranial aneurysms. Further enhancement of the detection of these key morphological structures was demonstrated by an optical-attenuation imaging variant of OCT. The presented techniques could provide further insights to the cause of intracranial aneurysm rupture and vascular healing mechanisms.

Late gadolinium enhancement (LGE) with cardiac magnetic resonance (CMR) imaging is the clinical reference for assessment of myocardial scar and focal fibrosis. However, current LGE techniques are confined to imaging of a single cardiac phase, which hampers assessment of scar motility and does not allow cross-comparison between multiple phases. In this work, we investigate a three step approach to obtain cardiac phase-resolved LGE images: (1) Acquisition of cardiac phase-resolved imaging data with varying T1 weighting. (2) Generation of semi-quantitative maps for each cardiac phase. (3) Synthetization of LGE contrast to obtain functional LGE images. The proposed method is evaluated in phantom imaging, six healthy subjects at 3T and 20 patients at 1.5T. Phantom imaging at 3T demonstrates consistent contrast throughout the cardiac cycle with a coefficient of variation of 2.55 ± 0.42%. In-vivo results show reliable LGE contrast with thorough suppression of the myocardial tissue is healthy subjects. The contrast between blood and myocardium showed moderate variation throughout the cardiac cycle in healthy subjects (coefficient of variation 18.2 ± 3.51%). Images were acquired at 40–60 ms and 80 ms temporal resolution, at 3T and 1.5, respectively. Functional LGE images acquired in patients with myocardial scar visualized scar tissue throughout the cardiac cycle, albeit at noticeably lower imaging resolution and noise resilience than the reference technique. The proposed technique bears the promise of integrating the advantages of phase-resolved CMR with LGE imaging, but further improvements in the acquisition quality are warranted for clinical use.

Choroid neovascularization (CNV) is caused by new blood vessels growing in the choroid and penetrating the bruch membrane. It is the major cause of vision disability in many retinal diseases. Though anti-vascular endothelial growth factor injection has proved to be effective for treating CNV, treatment planning is essential to ensure the efficacy while reducing the risk. For this purpose, we propose a CNV growth model based on longitudinal optical coherence tomography (OCT) images. The reaction-diffusion model is applied to simulate the growth and shrinkage of CNV volumes, and is solved by using the finite-element method. A fitted curve of the CNV growth/shrinkage rate is obtained by optimizing the growth parameters. Then, the trained parameters are applied to the predicted image to get the simulated image, which is compared with the validated image to evaluate the accuracy of prediction. The proposed method was tested on a dataset with seven patients in which each patient has 12 longitudinal OCT images. The resulted mean dice coefficient is 76.40%±8.20%. The experimental results show a promising step towards the image-guided patient-specific treatment.

It has been recently proposed that computer-simulated phantom images can be used to evaluate methods for fMRI preprocessing. It is widely recognized that Gradient-Echo Echo Planar Imaging (EPI), the most often used technique for fMRI, is strongly affected by field inhomogeneities. Accurate and realistic phantom images for use by the fMRI community for software evaluation and training must incorporate these distortions and account for the effects of head motion and respiration on the distortions. A method to generate realistic distortions caused by field inhomogeneity for the generation of an fMRI phantom is presented in this paper. Changes in field inhomogeneity due to motion are studied by means of adding motions to the brain model and calculating the induced field map numerically rather than measuring it experimentally. A fast analytic version of an MR simulation is used to generate distorted EPI images based on the calculated field maps. The new generated fMRI phantoms can be used to evaluate processing algorithms for fMRI study more accurately. We can appreciate the importance of distortions for fMRI phantom generation by simulating a distortion-free image and adding distortions afterwards. Validations are performed by comparing the calculated field maps with measured ones. In addition, we show the similarities between a simulated fMRI phantom and real EPI image from our MR scanner.

Statistical image reconstruction for computed tomography and positron emission tomography (CT/PET) play a significant role in the image quality by using spatial regularization that penalizes image intensity difference between neighboring pixels. The most commonly used quadratic membrane (QM) prior, which smooth’s both high frequency noise and edge details, tends to produce an unfavourable result while edge-preserving non-quadratic priors tend to produce blocky piecewise regions. However, these edge-preserving priors mostly depend on local smoothness or edges. It does not consider the basic fine structure information of the desired image, such as the gray levels, edge indicator, dominant direction and frequency. To address the aforementioned issues of the conventional regularizations/priors, this paper introduces and evaluates a hybrid approach to regularized ordered subset expectation maximization (OSEM) iterative reconstruction technique, which is an accelerated version of EM, with Poisson variability. Regularization is achieved by penalizing OSEM with probabilistic patch-based regularization (PPB) filter to form hybrid method (OSEM+PPB) for CT/PET image reconstruction that uses neighborhood patches instead of individual pixels in computing the non-quadratic penalty. The aim of this paper is to impose an effective edge preserving and noise removing framework to optimize the quality of CT/PET reconstructed images. A comparative analysis of the proposed model with some other existing standard methods in literature is presented both qualitatively and quantitatively using simulated test phantom and standard digital image. An experimental result indicates that the proposed method yields significantly improvements in quality of reconstructed images from the projection data. The obtained results justify the applicability of the proposed method.

In recent clinical practice of ultrasound imaging, the importance of high-frame-rate imaging is growing. Simultaneous multiple transmission is one way to increase frame rate while maintaining a spatial resolution and signal-to-noise ratio. However, this technique has an inherent issue in that "cross-talk artifacts" appear between the multiple transmitted pulses. In this study, a novel method providing higher-frame-rate ultrasound imaging with reduced cross-talk by combining a synthetic aperture and spatial coded excitation is proposed. In the proposed method, two coded transmission beams are simultaneously excited during beam steering in the lateral direction. Parallel receive beamforming is then performed in the region around individual transmission beams. Decoding is carried out by using two beamformed signals from a region where laterally neighboring transmission beams overlap. All decoded beamformed signals are then synthesized coherently. The proposed method was evaluated using a simulated phantom image under the assumption of imaging with a general sector probe. Results showed that the method achieved twice the frame rate while maintaining image resolution (105%) and reducing cross-talk artifacts from −37 dB to less than −57 dB.

Optical coherence tomography (OCT) is becoming one of the most important detection modalities for fast and noninvasive assessment of ophthalmological diseases. Diabetic macular edema (DME) is one of the important reasons leads to blindness. Its pathological features are mainly manifested in the accumulation of fluid in the retina. An automated method is proposed to identify and quantify the volume of cystoid macular edema in Spectral Domain OCT (SD-OCT) images. In the first stage of preprocessing, we balance the apparent signal-to-noise of each retinal OCT image. Because the signal-to-noise of OCT images is variable from patient to patient, and balance of the signal-to-noise ensures consistent segmentation of cystoid fluid. Speckle noise is the main reason leads to quality degrading in OCT images. The denoising method should be efficient for the noise suppression, and the edge information can be preserved at the same time. Then we used the anisotropic diffusion filter to suppress shot noise. The intensity inhomogeneity in OCT images may lead to false detection in the further segmentation work. Then we used the gamma transformation to change the brightness, which eliminates the effect availably. In the second stage of segmentation, we solve the problem of segmentation effectively by the improved level set method and calculated the area of edema area, which provides quantitative analytic tools for clinical diagnosis and therapy. Finally, the proposed method was evaluated on 15 SD-OCT retinal images from DME adults. Leave-one-out evaluation resulted in a precision, sensitivity and dice similarity coefficient (DSC) of 81.12%, 86.90% and 80.05%, respectively.

In preclinical vision research, cell grading in small animal models is essential for the quantitative evaluation of intraocular inflammation. Here, we present a new and practical optical coherence tomography (OCT) image analysis method for the automated detection and counting of aqueous cells in the anterior chamber (AC) of a rodent model of uveitis. Anterior segment OCT images are acquired with a 100 kHz swept-source OCT system. The proposed method consists of 2 steps. In the first step, we first despeckle and binarize each OCT image. After removing AS structures in the binary image, we then apply area thresholding to isolate cell-like objects. Potential cell candidates are selected based on their best fit to roundness. The second step performs the cell counting within the whole AC, in which additional cell tracking analysis is conducted on the successive OCT images to eliminate redundancy in cell counting. Finally, 3D cell grading using the proposed method is demonstrated in longitudinal OCT imaging of a mouse model of anterior uveitis in vivo. Rendering of anterior segment (orange) of mouse eye and automatically counted anterior chamber cells (green). Inset is a top view of the rendering, showing the cell distribution across the anterior chamber.

The phase images of cells and tissues are of great importance for obtaining their morphological and dynamics information. However, because of the uniform optical path-length of a light field passing through the inhomogeneous cells whose nuclei’ shape and structure are different but with equivalent physical thickness, we can not identify their subgroup just from their phase images, since their wrapped phase images have similar shape. Thus we put out a new idea that uses their scattering distributions as a auxiliary criterion for identifying cells with different nuclei structure. We built the ellipsoidal models to denote the cells’ external shape and placed three kinds of nuclei, such as hexahedron, cylinder and spheroid, into the center of ellipsoids to compose nucleated leucocytes. Employing the VirtualLab software to carry out the simulations, we first prove that, for cells with different nuclei structures, their wrapped phase distributions indeed have similar shape. Then after analyzing the results of scattering simulations, we obtain some important scattering characteristics related with their different nuclei’ shape and structures which are very useful for helping us to identify blood cells’ subgroup and can also provide good guidance for experimental research on inhomogeneous cells.

Chronic Kidney Disease (CKD) is characterized by a progressive loss in renal function over time. Pathology can provide valuable insights into the progression of CKD by analyzing the status of glomeruli and the uriniferous tubules over time. Optical coherence tomography (OCT) is a new procedure that can analyze the microscopic structure of the kidney in a non-invasive manner. This is especially important because there are significant artifacts associated with excision biopsies and immersion fixation procedures. Recently, we have shown that OCT can provide real time images of kidney microstructure and Doppler OCT (DOCT) can image glomerular renal blood flow <i>in vivo</i> without administrating exogenous contrast agents. In this study, we used OCT to evaluate CKD in a model induced by intravenous Adriamycin injection into Munich-Wistar rats. We evaluated tubular density and tubular diameter from OCT images at several post- Adriamycin induction time points and compared them with conventional light microscopic histological imaging. Proteinurea and serum creatinine were used as physiological markers of the extent of CKD. Preliminary OCT results revealed changes in tubular density due to tubular necrosis and interstitial fibrosis within the first 4 weeks following Adriamycin injection. From week 4 to 8 after Adriamycin induction, changes in tubular density and diameter occurred due to both tubular loss and tubular dilation. The results suggest OCT can provide additional information about kidney histopathology in CKD. DOCT revealed reduced blood flow in some glomeruli probably as a consequence of focal glomerularsclerosis.

A forward-imaging needle-type optical coherence tomography (OCT) probe with Doppler OCT (DOCT) capability has the potential to solve critical challenges in interventional procedures. A case in point is stereotactic neurosurgery where probes are advanced into the brain based on predetermined coordinates. Laceration of blood vessels in front of the advancing probe is an unavoidable complication with current methods. Moreover, cerebrospinal fluid (CSF) leakage during surgery can shift the brain rendering the predetermined coordinates unreliable. In order to address these challenges, we developed a forward-imaging OCT probe (740 μm O.D.) using a gradient-index (GRIN) rod lens that can provide real-time imaging feedback for avoiding at-risk vessels (8 frames/s with 1024 A-scans per frame for OCT/DOCT dual imaging) and guiding the instrument to specific targets with 12 μm axial resolution (100 frames/s with 160 A-scans per frame for OCT imaging only). The high signal-to-background characteristic of DOCT provides exceptional sensitivity in detecting and quantifying the blood flow within the sheep brain parenchyma in real time. The OCT/DOCT dual imaging also demonstrated its capability to differentiate the vessel type (artery/vein) on rat's femoral vessels. We also demonstrated in ex vivo human brain that the location of the tip of the OCT probe can be inferred from micro-anatomical landmarks in OCT images. These findings demonstrate the suitability of OCT guidance during stereotactic procedures in the brain and its potential for reducing the risk of cerebral hemorrhage.