MR imaging of left-ventricular function : novel image acquisition and analysis techniques.

Many cardiac diseases, such as myocardial ischemia, secondary to coronary artery disease, may be identified and localized through the analysis of cardiac deformations. Early efforts for quantifying ventricular wall motion used surgical implantation and tracking of radiopaque markers with X-ray imaging in canine hearts [1]. Such techniques are invasive and affect the regional motion pattern of the ventricular wall during the marker tracking process and, clearly are not feasible clinically. Noninvasive imaging techniques are vital and have been widely applied to the clinic. MRI is a noninvasive imaging technique with the capability to monitor and assess the progression of cardiovascular diseases (CVD) so that effective procedures for the care and treatment of patients can be developed by physicians and researchers. It is capable of providing 3D analysis of global and regional cardiac function with great accuracy and reproducibility. In the past few years, numerous efforts have been devoted to cardiac motion recovery and deformation analysis from MR imaging sequences. In order to assess cardiac function, there are two categories of indices that are used: global and regional indices. Global indices include ejection fraction, cavity volume, and myocardial mass [2]. They are important indices for cardiac disease diagnosis. However, these global indices are not specific for regional analysis. A quantitative assessment of regional parameters may prove beneficial for the diagnosis of disease and evaluation of severity and the quantification of treatment [3]. Local measures, such as wall deformation and strain in all regions of the heart, can provide objective regional quantification of ventricular wall function and relate to the location and extent of ischemic injury. This dissertation is concerned with the development of novel MR imaging techniques and image postprocessing algorithms to analyze left ventricular deformations. A novel pulse sequence, termed Orthogonal CSPAMM (OCSPAMM), has been proposed which results in the same acquisition time as SPAMM for 2D deformation estimation while keeping the main advantages of CSPAMM [4,5]: i.e., maintaining tag contrast through-out the ECG cycle. Different from CSPAMM, in OCSPAMM the second tagging pulse orientation is rotated 90 degrees relative to the first one so that motion information can be obtained simultaneously in two directions. This reduces the acquisition time by a factor of two as compared to the traditional CSPAMM, in which two separate imaging sequences are applied per acquisition. With the application of OCSPAMM, the effect of tag fading encountered in SPAMM tagging due to Tl relaxation is mitigated and tag deformations can be visualized for the entire cardiac cycle, including diastolic phases. A multilevel B-spline fitting method (MBS) has been proposed which incorporates phase-based displacement information for accurate calculation of 2D motion and strain from tagged MRI [6, 7]. The proposed method combines the advantages of continuity and smoothness of MBS, and makes use of phase information derived from tagged MR images. Compared to previous 2D B-spline-based deformation analysis methods, MBS has the following advantages: 1) It can simultaneously achieve a smooth deformation while accurately approximating the given data set; 2) Computationally, it is very fast; and 3) It can produce more accurate deformation results. Since the tag intersections (intersections between two tag lines) can be extracted accurately and are more or less distributed evenly over the myocardium, MBS has proven effective for 2D cardiac motion tracking. To derive phase-based displacements, 2D HARP and SinMod analysis techniques [8,9] were employed. By producing virtual tags from HARP /SinMod and calculating intersections of virtual tag lines, more data points are obtained. In the reference frame, virtual tag lines are the isoparametric curves of an undeformed 2D B-spline model. In subsequent frames, the locations of intersections of virtual tag lines over the myocardium are updated with phase-based displacement. The advantage of the technique is that in acquiring denser myocardial displacements, it uses both real and virtual tag line intersections. It is fast and more accurate than 2D HARP and SinMod tracking. A novel 3D sine wave modeling (3D SinMod) approach for automatic analysis of 3D cardiac deformations has been proposed [10]. An accelerated 3D complementary spatial modulation of magnetization (CSPAMM) tagging technique [11] was used to acquire complete 3D+t tagged MR data sets of the whole heart (3 dynamic CSPAMM tagged MRI volume with tags in different orientations), in-vivo, in 54 heart beats and within 3 breath-holds. In 3D SinMod, the intensity distribution around each pixel is modeled as a cosine wave front. The principle behind 3D SinMod tracking is that both phase and frequency for each voxel are determined directly from the frequency analysis and the displacement is calculated from the quotient of phase difference and local frequency. The deformation fields clearly demonstrate longitudinal shortening during systole. The contraction of the LV base towards the apex as well as the torsional motion between basal and apical slices is clearly observable from the displacements. 3D SinMod can automatically process the image data to derive measures of motion, deformations, and strains between consecutive pair of tagged volumes in 17 seconds. Therefore, comprehensive 4D imaging and postprocessing for determination of ventricular function is now possible in under 10 minutes. For validation of 3D SinMod, 7 3D+t CSPAMM data sets of healthy subjects have been processed. Comparison of mid-wall contour deformations and circumferential shortening results by 3D SinMod showed good agreement with those by 3D HARP. Tag lines tracked by the proposed technique were also compared with manually delineated ones. The average errors calculated for the systolic phase of the cardiac cycles were in the sub-pixel range

Development Of Optical Coherence Tomography For Tissue Diagnostics

Microvasculature can be found in almost every part of the human body, including the internal organs. Importantly, abnormal changes in microvasculature are usually related to pathological development of the tissue cells. Monitoring of changes in blood flow properties in microvasculature, therefore, provides useful diagnostic information about pathological conditions in biological tissues as exemplified in glaucoma, diabetes, age related macular degeneration, port wine stains, burn-depth, and potentially skin cancer. However, the capillary network is typically only one cell in wall thickness with 5 to 10 microns in diameter and located in the dermis region of skin. Therefore, a non-invasive flow imaging technique that is capable of depth sectioning at high resolution and high speed is demanded. Optical coherence tomography (OCT), particularly after its advancement in frequency domain OCT (FD-OCT), is a promising tool for non-invasive high speed, high resolution, and high sensitivity depth-resolved imaging of biological tissues. Over the last ten years, numerous efforts have been paid to develop OCTbased flow imaging techniques. An important effort is the development of phase-resolved Doppler OCT (PR-DOCT). Phase-resolved Doppler imaging using FD-OCT is particularly of interest because of the direct access to the phase information of the depth profile signal. Furthermore, the high speed capability of FD-OCT is promising for real time flow monitoring as well as 3D flow segmentation applications. However, several challenges need to be addressed; 1) Flow in biological samples exhibits a wide dynamic range of flow velocity caused by, for example, the iv variation in the flow angles, flow diameters, and functionalities. However, the improvement in imaging speed of FD-OCT comes at the expense of a reduction in sensitivity to slow flow information and hence a reduction in detectable velocity range; 2) A structural ambiguity socalled \u27mirror image\u27 in FD-OCT prohibits the use of maximum sensitivity and imaging depth range; 3) The requirement of high lateral resolution to resolve capillary vessels requires the use of an imaging optics with high numerical aperture (NA) that leads to a reduction in depth of focus (DOF) and hence the imaging depth range (i.e. less than 100 microns) unless dynamic focusing is performed. Nevertheless, intrinsic to the mechanism of FD-OCT, dynamic focusing is not possible. In this dissertation, the implementation of PR-DOCT in a high speed swept-source based FD-OCT is investigated and optimized. An acquisition scheme as well as a processing algorithm that effectively extends the detectable velocity dynamic range of the PR-DOCT is presented. The proposed technique increased the overall detectable velocity dynamic range of PR-DOCT by about five times of that achieved by the conventional method. Furthermore, a novel technique of mirror image removal called ‘Dual-Detection FD-OCT’ (DD-FD-OCT) is presented. One of the advantages of DD-FD-OCT to Doppler imaging is that the full-range signal is achieved without manipulation of the phase relation between consecutive axial lines. Hence the full-range DD-FDOCT is fully applicable to phase-resolved Doppler detection without a reduction in detectable velocity dynamic range as normally encountered in other full-range techniques. In addition, PRDOCT can utilize the maximum SNR provided by the full-range capability. This capability is particularly useful for imaging of blood flow that locates deep below the sample surface, such as v blood flow at deep posterior human eye and blood vessels network in the dermis region of human skin. Beside high speed and functional imaging capability, another key parameter that will open path for optical diagnostics using OCT technology is high resolution imaging (i.e. in a regime of a few microns or sub-micron). Even though the lateral resolution of OCT can be independently improved by opening the NA of the imaging optics, the high lateral resolution is maintained only over a short range as limited by the depth of focus that varies inversely and quadratically with NA. Recently developed by our group, ‘Gabor-Domain Optical Coherence Microscopy’ (GD-OCM) is a novel imaging technique capable for invariant resolution of about 2-3 m over a 2 mm cubic field-of-view. This dissertation details the imaging protocol as well as the automatic data fusion method of GD-OCM developed to render an in-focus high-resolution image throughout the imaging depth of the sample in real time. For the application of absolute flow measurement as an example, the precise information about flow angle is required. GDOCM provides more precise interpretation of the tissue structures over a large field-of-view, which is necessary for accurate mapping of the flow structure and hence is promising for diagnostic applications particularly when combined with Doppler imaging. Potentially, the ability to perform high resolution OCT imaging inside the human body is useful for many diagnostic applications, such as providing an accurate map for biopsy, guiding surgical and other treatments, monitoring the functional state and/or the post-operative recovery process of internal organs, plaque detection in arteries, and early detection of cancers in the gastrointestinal tract. Endoscopic OCT utilizes a special miniature probe in the sample arm to vi access tubular organs inside the human body, such as the cardiovascular system, the lung, the gastrointestinal tract, the urinary tract, and the breast duct. We present an optical design of a dynamic focus endoscopic probe that is capable of about 4 to 6 m lateral resolution over a large working distance (i.e. up to 5 mm from the distal end of the probe). The dynamic focus capability allows integration of the endoscopic probe to GD-OCM imaging to achieve high resolution endoscopic tomograms. We envision the future of this developing technology as a solution to high resolution, minimally invasive, depth-resolved imaging of not only structure but also the microvasculature of in vivo biological tissues that will be useful for many clinical applications, such as dermatology, ophthalmology, endoscopy, and cardiology. The technology is also useful for animal study applications, such as the monitoring of an embryo’s heart for the development of animal models and monitoring of changes in blood circulation in response to external stimulus in small animal brains

Short-coherence off-axis holographic phase microscopy of live cell dynamics

We demonstrate a single-shot holographic phase microscope that combines short-coherence laser pulses with an off-axis geometry. By introducing a controlled pulse front tilt, ultrashort pulses are made to interfere over a large field-of-view without loss of fringe contrast. With this microscope, quantitative phase images of live cells can be recorded in a fullfield geometry without moving parts. We perform phase imaging of HEK293 cells, to study the dynamics of cell volume regulation in response to an osmotic shock

Seismic characterisation based on time-frequency spectral analysis

We present high-resolution time-frequency spectral analysis schemes to better resolve seismic images for the purpose of seismic and petroleum reservoir characterisation. Seismic characterisation is based on the physical properties of the Earth's subsurface media, and these properties are represented implicitly by seismic attributes. Because seismic traces originally presented in the time domain are non-stationary signals, for which the properties vary with time, we characterise those signals by obtaining seismic attributes which are also varying with time. Among the widely used attributes are spectral attributes calculated through time-frequency decomposition. Time-frequency spectral decomposition methods are employed to capture variations of a signal within the time-frequency domain. These decomposition methods generate a frequency vector at each time sample, referred to as the spectral component. The computed spectral component enables us to explore the additional frequency dimension which exists jointly with the original time dimension enabling localisation and characterisation of patterns within the seismic section. Conventional time-frequency decomposition methods include the continuous wavelet transform and the Wigner-Ville distribution. These methods suffer from challenges that hinder accurate interpretation when used for seismic interpretation. Continuous wavelet transform aims to decompose signals on a basis of elementary signals which have to be localised in time and frequency, but this method suffers from resolution and localisation limitations in the time-frequency spectrum. In addition to smearing, it often emerges from ill-localisation. The Wigner-Ville distribution distributes the energy of the signal over the two variables time and frequency and results in highly localised signal components. Yet, the method suffers from spurious cross-term interference due to its quadratic nature. This interference is misleading when the spectrum is used for interpretation purposes. For the specific application on seismic data the interference obscures geological features and distorts geophysical details. This thesis focuses on developing high fidelity and high-resolution time-frequency spectral decomposition methods as an extension to the existing conventional methods. These methods are then adopted as means to resolve seismic images for petroleum reservoirs. These methods are validated in terms of physics, robustness, and accurate energy localisation, using an extensive set of synthetic and real data sets including both carbonate and clastic reservoir settings. The novel contributions achieved in this thesis include developing time-frequency analysis algorithms for seismic data, allowing improved interpretation and accurate characterisation of petroleum reservoirs. The first algorithm established in this thesis is the Wigner-Ville distribution (WVD) with an additional masking filter. The standard WVD spectrum has high resolution but suffers the cross-term interference caused by multiple components in the signal. To suppress the cross-term interference, I designed a masking filter based on the spectrum of the smoothed-pseudo WVD (SP-WVD). The original SP-WVD incorporates smoothing filters in both time and frequency directions to suppress the cross-term interference, which reduces the resolution of the time-frequency spectrum. In order to overcome this side-effect, I used the SP-WVD spectrum as a reference to design a masking filter, and apply it to the standard WVD spectrum. Therefore, the mask-filtered WVD (MF-WVD) can preserve the high-resolution feature of the standard WVD while suppressing the cross-term interference as effectively as the SP-WVD. The second developed algorithm in this thesis is the synchrosqueezing wavelet transform (SWT) equipped with a directional filter. A transformation algorithm such as the continuous wavelet transform (CWT) might cause smearing in the time-frequency spectrum, i.e. the lack of localisation. The SWT attempts to improve the localisation of the time-frequency spectrum generated by the CWT. The real part of the complex SWT spectrum, after directional filtering, is capable to resolve the stratigraphic boundaries of thin layers within target reservoirs. In terms of seismic characterisation, I tested the high-resolution spectral results on a complex clastic reservoir interbedded with coal seams from the Ordos basin, northern China. I used the spectral results generated using the MF-WVD method to facilitate the interpretation of the sand distribution within the dataset. In another implementation I used the SWT spectral data results and the original seismic data together as the input to a deep convolutional neural network (dCNN), to track the horizons within a 3D volume. Using these application-based procedures, I have effectively extracted the spatial variation and the thickness of thinly layered sandstone in a coal-bearing reservoir. I also test the algorithm on a carbonate reservoir from the Tarim basin, western China. I used the spectrum generated by the synchrosqueezing wavelet transform equipped with directional filtering to characterise faults, karsts, and direct hydrocarbon indicators within the reservoir. Finally, I investigated pore-pressure prediction in carbonate layers. Pore-pressure variation generates subtle changes in the P-wave velocity of carbonate rocks. This suggests that existing empirical relations capable of predicting pore-pressure in clastic rocks are unsuitable for the prediction in carbonate rocks. I implemented the prediction based on the P-wave velocity and the wavelet transform multi-resolution analysis (WT-MRA). The WT-MRA method can unfold information within the frequency domain via decomposing the P-wave velocity. This enables us to extract and amplify hidden information embedded in the signal. Using Biot's theory, WT-MRA decomposition results can be divided into contributions from the pore-fluid and the rock framework. Therefore, I proposed a pore-pressure prediction model which is based on the pore-fluid contribution, calculated through WT-MRA, to the P-wave velocity.Open Acces

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Optical imaging techniques in microfluidics and their applications

Microfluidic devices have undergone rapid development in recent years and provide a lab-on-a-chip solution for many biomedical and chemical applications. Optical imaging techniques are essential in microfluidics for observing and extracting information from biological or chemical samples. Traditionally, imaging in microfluidics is achieved by bench-top conventional microscopes or other bulky imaging systems. More recently, many novel compact microscopic techniques have been developed to provide a low-cost and portable solution. In this review, we provide an overview of optical imaging techniques used in microfluidics followed with their applications. We first discuss bulky imaging systems including microscopes and interferometer-based techniques, then we focus on compact imaging systems that can be better integrated with microfluidic devices, including digital in-line holography and scanning-based imaging techniques. The applications in biomedicine or chemistry are also discussed along with the specific imaging techniques