Stick Based Speckle Reduction for Real-Time Processing of OCT Images on an FPGA

This paper presents an FPGA based real-time implementation of an adaptive speckle reduction algorithm. Applied to the log-compressed image of a high-resolution optical coherence tomography (OCT) system, all related signal processing steps from envelope detection to VGA video signal generation are executed on a single chip. Images from measured OCT data show that the chosen algorithm produces a smooth, detailed image with fewer image artifacts than comparable approaches. An estimation of the hardware effort, the possible throughput rate and the resulting image frame rate is given for different window sizes used here in speckle reduction.

Method for Narrow Vascular Structure Segmentation in Ct Data.

International audienc

Ultrasound Imaging

In this book, we present a dozen state of the art developments for ultrasound imaging, for example, hardware implementation, transducer, beamforming, signal processing, measurement of elasticity and diagnosis. The editors would like to thank all the chapter authors, who focused on the publication of this book

Coronary angiography enhancement for visualization

High quality visualization on X-ray angiograms is of great significance both for the diagnosis of vessel abnormalities and for coronary interventions. Algorithms for improving the visualization of detailed vascular structures without significantly increasing image noise are currently demanded in the market. A new algorithm called stick-guided lateral inhibition (SGLI) is presented for increasing the visibility of coronary vascular structures. A validation study was set up to compare the SGLI algorithm with the conventional unsharp masking (UM) algorithm on 20 still frames of coronary angiographic images. Ten experienced QCA analysts and nine cardiologists from various centers participated in the validation. Sample scoring value (SSV) and observer agreement value (OAV) were defined to evaluate the validation result, in terms of enhancing performance and observer agreement, respectively. The mean of SSV was concluded to be 77.1 ± 11.9%, indicating that the SGLI algorithm performed significantly better than the UM algorithm (P-value < 0.001). The mean of the OAV was concluded to be 70.3%, indicating that the average agreement with respect to a senior cardiologist was 70.3%. In conclusion, this validation study clearly demonstrates the superiority of the SGLI algorithm in the visualization of coronary arteries from X-ray angiograms

Semi-supervised segmentation of ultrasound images based on patch representation and continuous min cut.

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the segmentation. However, such priors tend to limit these methods to a specific target or imaging settings, and they are not always applicable to pathological cases. This work introduces a semi-supervised segmentation framework for ultrasound imaging that alleviates the limitation of fully automatic segmentation, that is, it is applicable to any kind of target and imaging settings. Our methodology uses a graph of image patches to represent the ultrasound image and user-assisted initialization with labels, which acts as soft priors. The segmentation problem is formulated as a continuous minimum cut problem and solved with an efficient optimization algorithm. We validate our segmentation framework on clinical ultrasound imaging (prostate, fetus, and tumors of the liver and eye). We obtain high similarity agreement with the ground truth provided by medical expert delineations in all applications (94% DICE values in average) and the proposed algorithm performs favorably with the literature

Image segmentation and reconstruction of 3D surfaces from carotid ultrasound images

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

An Automated Modified Region Growing Technique for Prostate Segmentation in Trans-Rectal Ultrasound Images

Medical imaging plays a vital role in the medical field because it is widely used in diseases diagnosis and treatment of patients. There are different modalities of medical imaging such as ultrasounds, x-rays, Computed Tomography (CT), Magnetic Resonance (MR), and Positron Emission Tomography (PET). Most of these modalities usually suffer from noise and other sampling artifacts. The diagnosis process in these modalities depends mainly on the interpretation of the radiologists. Consequently, the diagnosis is subjective as it is based on the radiologist experience. Medical image segmentation is an important process in the field of image processing. It has a significant role in many applications such as diagnosis, therapy planning, and advanced surgeries. There are many segmentation techniques to be applied on medical images. However, most of these techniques are still depending on the experts, especially for initializing the segmentation process. The artifacts of images can affect the segmentation output. In this thesis, we propose a new approach for automatic prostate segmentation of Trans-Rectal UltraSound (TRUS) images by dealing with the speckle not as noise but as informative signals. The new approach is an automation of the conventional region growing technique. The proposed approach overcomes the requirement of manually selecting a seed point for initializing the segmentation process. In addition, the proposed approach depends on unique features such as the intensity and the spatial Euclidean distance to overcome the effect of the speckle noise of the images. The experimental results of the proposed approach show that it is fast and accurate. Moreover, it performs well on the ultrasound images, which has the common problem of the speckle noise

Pulsed Transcranial Ultrasound Stimulation and Its Applications in Treatment of Focal Cerebral Ischemia and Depression

The aims of this thesis were to investigate the therapeutic effects of pulsed transcranial ultrasound stimulation (pTUS) on focal cerebral ischemia and depression, respectively, in rodent models. Neurological and psychiatric disorders, such as Parkinson's disease, epilepsy, Alzheimer's disease, stroke (vascular disorder that results in neurological defects), depression, and etc., present an increasing challenge and a substantial social and economic burden for an aging and stressed population. However, conventional treatments, especially pharmacologic interventions, have significant limitations, such as nonspecific effects, insufficient tailoring to the individual, adverse effects such as drowsiness, weight gain and nausea, or inadequate uptake into the brain due to the blood-brain-barrier (BBB). In contrast, neuromodulation techniques have gained more attention, which are able to enhance or inhibit the neural activities in specific cortex, such as motor, somatosensory or other areas related to cognition. Neuromodulation thus could potentially restore the disrupted neural network due to neurological disorders. Capitalizing on its noninvasiveness, high precision (in the scale of mm) and penetration depth (several centimeters), low-intensity (typically <1 W/cm2 spatial-peak-pulse-average intensity-ISPTA) low-frequency (typically <1MHz), pulsed transcranial ultrasound stimulation (pTUS) has been emerging as a promising therapeutic tool for neurological and psychiatric disorders. This thesis provided the first in-vivo demonstrations that pTUS might serve as neuroprotective preconditioning of ischemic brain injury and treatment of depression. Additionally, it also proposed a novel optical imaging-based technique to characterize the neuromodulatory effect of pTUS, which facilitates the parameter optimization of therapeutic pTUS in practice. Both suppressive and excitatory pTUS are applied in this thesis. The corresponding pTUS parameters were: (a) suppressive pTUS (or pTUSS): ISPPA = 8W/cm2, frequency (f) = 0.5 MHz, pulse repetition frequency (PRF) = 100 Hz, and duty cycle (DC) =5%, and (b) excitatory pTUS (or pTUSE): ISPPA = 8W/cm2, f = 0.5MHz, PRF = 1.5 kHz, and DC = 60%, respectively. Before the therapeutic experiments, the neuromodulatory effects of both pTUSS and pTUSE were examined using laser speckle imaging(LSCI) and multispectral reflectance imaging (MSRI) in aspect of the neurovascular responses. Specifically, this thesis consists of: (1) Study on the neurovascular response to pTUS. Compared with other methods, such as pTUS-triggered motor response and visual evoked potentials (VEP), optical imaging allows to measure the neurovascular change at high spatiotemporal resolution (in the scale of μm and ms), including cortical suppression without evoked output. LSCI and MSRI were used to monitor the primary somatosensory response (Chapter 2) to hind limb electrical stimulation before, immediately, and 1 h after 5-min application of pTUSS and pTUSE, respectively. Several indicators, including Response Index, Peak Response, Latency and Response Duration, were derived from optical images to characterize the neuromodulatory effects of pTUS on primary somatosensory cortex. Our results showed that pTUSS could suppress the primary somatosensory cortex across all rats whereas pTUSE only presented excitatory effects in 5 out of 11 rats. The neuromodulatory effects of pTUS were correlated with the baseline cortical excitability. The results showed that: (i) pTUSs could serve in investigating cognitive function by silencing the neurons in the target region; (ii) pTUSE exposure should be treated with caution due to individual differences in neuromodulatory effects, which were associated with the initial brain state of rats; and (iii) optical imaging was useful in evaluating the pTUS neuromodulatory effects. (2) Neuroprotection of preconditioning pTUS. By applying suppressive pTUS, it was investigated whether the severity of stroke could be minimized or alleviated by prior exposure to ultrasound stimulation (Chapter 3). Preconditioning was supposed to increase the tolerance of brain to subsequent ischemic insult. It can potentially be used to prevent the perioperative stroke in patients undergoing cardiovascular surgeries with a series of complications. Considering the noninvasiveness and safety of ultrasound, pTUS may provide a novel preconditioning method. To test the effectiveness of preconditioning pTUS, rats were randomly assigned to control (n=12) and preconditioning pTUS (pTUS-PC) groups (n=14). The pTUS-PC animals received ultrasound stimulation before the induction of photothrombotic stroke, whereas control animals were handled identically except the ultrasound stimulation. The cerebral blood flow was monitored using LSCI in both groups during stroke induction, as well as 24 hours and 48 hours after stroke, respectively. Also, infarct volumes and edema were measured at 48 hours after euthanatizing the rats. Results showed that pTUS-PC rats had smaller ischemic volume during stroke induction, as well as 24 hours and 48 hours after the stroke than the controls. Moreover, the pTUS-PC group showed lower volume of brain edema than the control group. (3) Antidepressant-like effect by pTUS. The potential antidepressant-like effects of pTUS were further investigated in a rat model of depression with excitatory pTUS. Stimulating the left prefrontal cortex (PFC) by TMS has been clinically used for depression treatment, it was thus hypothesize that pTUSE on PFC would act similarly with TMS and result in antidepressant-like effect. To test this hypothesis, pTUS was applied for 2 weeks daily to the left PFC of depressed rats induced by 48-hour restraint. The long-term (3 weeks) efficacy of the depression model as well as the antidepressant-like effects of pTUS were investigated with a group of behavioral tests. In addition, the hippocampal BDNF was measured by western blot to study the mechanisms underlying antidepressant-like effects of pTUS. The safety of long-term (2 weeks) pTUS was assessed by histologic analysis. Results showed that 48-hour-restraint stress could stably lead to at least 3-week reduction of exploratory behavior and protracted anhedonia, whereas pTUSE treatment could successfully reverse the depression-like phenotypes and promote the BDNF expression in the left hippocampus. In addition, H& E staining of brain tissues confirmed the safety of the long-term pTUS treatment. In conclusion, the results in this work suggested that pTUS could serve as preconditioning of perioperative stroke and therapeutics for depression. Additionally, the results also demonstrated that optical neurovascular imaging could measure the neuromodulatory effect of pTUS. This study documented more evidence that pTUS is a promising tool for basic neuroscience and therapeutic applications. KEY WORDS: Neurological and psychiatric disorders, brain stimulation, pulsed ultrasound stimulation, neurovascular imaging, preconditioning, stroke, depression.Ph.D., Biomedical Engineering -- Drexel University, 201

An Information Tracking Approach to the Segmentation of Prostates in Ultrasound Imaging

Outlining of the prostate boundary in ultrasound images is a very useful procedure performed and subsequently used by clinicians. The contribution of the resulting segmentation is twofold. First of all, the segmentation of the prostate glands can be used to analyze the size, geometry, and volume of the gland. Such analysis is useful as it is known that the former quantities used in conjunction with a PSA blood test can be used as an indicator of malignancy in the gland itself. The second purpose of accurate segmentation is for treatment planning purposes. In brachetherapy, commonly used to treat localized prostate cancer, the accurate location of the prostate must be found so that the radioactive seeds can be placed precisely in the malignant regions. Unfortunately, the current method of segmentation of ultrasound images is performed manually by expert radiologists. Due to the abundance of ultrasound data, the process of manual segmentation can be extremely time consuming and inefficient. A much more desirable way to perform the segmentation process is through automatic procedures, which should be able to accurately and efficiently extract the boundary of the prostate gland with minimal user intervention. This is the ultimate goal of the proposed approach. The proposed segmentation algorithm uses a probability distribution tracking framework to accurately and efficiently perform the task at hand. The basis for this methodology is to extract image and shape features from available manually segmented ultrasound images for which the actual prostate region is known. Then, the segmentation algorithm seeks a region in new ultrasound images whose features closely mirror the learned features of known prostate regions. Promising results were achieved using this method in a series of in silico and in vivo experiments