Coherent correlator design analysis for the implementation of deep learning networks.

Optical signal processing can reduce the electrical power consumption required over that required by graphically processing units. There remain a number of challenges to overcome. Noise is potentially much larger in optical systems than in their electronic counterparts, and some of the operations, such as a bias addition, are not easy to implement in free space processors. This paper analyzes a proposed design that utilizes a camera and lightweight electronic processing to perform the convolutional layers. Simulations are performed to compare the expected performance against an ideal system that cannot be physically realized and a proposed architecture. The impact of speckle noise in the system is analyzed and methods to reduce this are proposed.

Multiple-view polarimetric camera.

A multiple-view polarimetric camera is developed. The system uses four separate action cameras, and software is employed to map the images onto each other in order to generate the Stokes vectors, the degree of linear polarization, and the angle images. To ensure robustness, an automated calibration system has been developed that ensures the pixels are correctly mapped. Video frame synchronization is also developed.

Long-distance Bessel beam propagation through Kolmogorov turbulence.

Free-space optical communication has the potential to transmit information with both high speed and security. However, since it is unguided it suffers from losses due to atmospheric turbulence and diffraction. To overcome the diffraction limits the long-distance propagation of Bessel beams is considered and compared against Gaussian beam properties. Bessel beams are shown to have a number of benefits over Gaussian beams when propagating through atmospheric turbulence.

Service oriented architecture for clinical decision support: a systematic review and future directions.

The use of a service-oriented architecture (SOA) has been identified as a promising approach for improving health care by facilitating reliable clinical decision support (CDS). A review of the literature through October 2013 identified 44 articles on this topic. The review suggests that SOA related technologies such as Business Process Model and Notation (BPMN) and Service Component Architecture (SCA) have not been generally adopted to impact health IT systems' performance for better care solutions. Additionally, technologies such as Enterprise Service Bus (ESB) and architectural approaches like Service Choreography have not been generally exploited among researchers and developers. Based on the experience of other industries and our observation of the evolution of SOA, we found that the greater use of these approaches have the potential to significantly impact SOA implementations for CDS.

A service oriented approach for guidelines-based clinical decision support using BPMN.

Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS).

Grey-matter texture abnormalities and reduced hippocampal volume are distinguishing features of schizophrenia.

Neurodevelopmental processes are widely believed to underlie schizophrenia. Analysis of brain texture from conventional magnetic resonance imaging (MRI) can detect disturbance in brain cytoarchitecture. We tested the hypothesis that patients with schizophrenia manifest quantitative differences in brain texture that, alongside discrete volumetric changes, may serve as an endophenotypic biomarker. Texture analysis (TA) of grey matter distribution and voxel-based morphometry (VBM) of regional brain volumes were applied to MRI scans of 27 patients with schizophrenia and 24 controls. Texture parameters (uniformity and entropy) were also used as covariates in VBM analyses to test for correspondence with regional brain volume. Linear discriminant analysis tested if texture and volumetric data predicted diagnostic group membership (schizophrenia or control). We found that uniformity and entropy of grey matter differed significantly between individuals with schizophrenia and controls at the fine spatial scale (filter width below 2mm). Within the schizophrenia group, these texture parameters correlated with volumes of the left hippocampus, right amygdala and cerebellum. The best predictor of diagnostic group membership was the combination of fine texture heterogeneity and left hippocampal size. This study highlights the presence of distributed grey-matter abnormalities in schizophrenia, and their relation to focal structural abnormality of the hippocampus. The conjunction of these features has potential as a neuroimaging endophenotype of schizophrenia.

An image reconstruction algorithm for 3-D electrical impedance mammography.

The Sussex MK4 electrical impedance mammography system is especially designed for 3-D breast screening. It aims to diagnose breast cancer at an early stage when it is most treatable. Planar electrodes are employed in this system. The challenge with planar electrodes is the inaccuracy and poor sensitivity in the vertical direction for 3-D imaging. An enhanced image reconstruction algorithm using a duo-mesh method is proposed to improve the vertical accuracy and sensitivity. The novel part of the enhanced image reconstruction algorithm is the correction term. To evaluate the new algorithm, an image processing based error analysis method is presented, which not only can precisely assess the error of the reconstructed image but also locate the center and outline the center and outline the shape of the objects of interest. Although the enhanced image reconstruction algorithm and the image processing based error analysis method are designed for the Sussex MK4 system, they are applicable to all electrical impedance tomography systems, regardless of the hardware design. To validate the enhanced algorithm, performance results from simulations, phantoms and patients are presented.

Enabling Healthcare IT Governance: Human Task Management Service for Administering Emergency Department's Resources for Efficient Patient Flow.

The use of Health Information Technology (HIT) to improve healthcare service delivery is constantly increasing due to research advances in medical science and information systems. Having a fully automated process solution for a Healthcare Organization (HCO) requires a combination of organizational strategies along with a selection of technologies that facilitate the goal of improving clinical outcomes. HCOs, requires dynamic management of care capability to realize the full potential of HIT. Business Process Management (BPM) is being increasingly adopted to streamline the healthcare service delivery and management processes. Emergency Departments (EDs) provide a case in point, which require multidisciplinary resources and services to deliver effective clinical outcomes. Managed care involves the coordination of a range of services in an ED. Although fully automated processes in emergency care provide a cutting edge example of service delivery, there are many situations that require human interactions with the computerized systems; e.g. Medication Approvals, care transfer, acute patient care. This requires a coordination mechanism for all the resources, computer and human, to work side by side to provide the best care. To ensure evidence-based medical practice in ED, we have designed a Human Task Management service to model the process of coordination of ED resources based on the UK's NICE Clinical guideline for managing the care of acutely ill patients. This functionality is implemented using Java Business process Management (jBPM).

Abnormalities in fronto-striatal connectivity within language networks relate to differences in grey-matter heterogeneity in Asperger syndrome.

Asperger syndrome (AS) is an Autism Spectrum Disorder (ASD) characterised by qualitative impairment in the development of emotional and social skills with relative preservation of general intellectual abilities, including verbal language. People with AS may nevertheless show atypical language, including rate and frequency of speech production. We previously observed that abnormalities in grey matter homogeneity (measured with texture analysis of structural MR images) in AS individuals when compared with controls are also correlated with the volume of caudate nucleus. Here, we tested a prediction that these distributed abnormalities in grey matter compromise the functional integrity of brain networks supporting verbal communication skills. We therefore measured the functional connectivity between caudate nucleus and cortex during a functional neuroimaging study of language generation (verbal fluency), applying psycho-physiological interaction (PPI) methods to test specifically for differences attributable to grey matter heterogeneity in AS participants. Furthermore, we used dynamic causal modelling (DCM) to characterise the causal directionality of these differences in interregional connectivity during word production. Our results revealed a diagnosis-dependent influence of grey matter heterogeneity on the functional connectivity of the caudate nuclei with right insula/inferior frontal gyrus and anterior cingulate, respectively with the left superior frontal gyrus and right precuneus. Moreover, causal modelling of interactions between inferior frontal gyri, caudate and precuneus, revealed a reliance on bottom-up (stimulus-driven) connections in AS participants that contrasted with a dominance of top-down (cognitive control) connections from prefrontal cortex observed in control participants. These results provide detailed support for previously hypothesised central disconnectivity in ASD and specify discrete brain network targets for diagnosis and therapy in ASD.

Investigation of voltage source design's for Electrical Impedance Mammography (EIM) Systems.

According to Jossient, interesting characteristics of breast tissues mostly lie above 1MHz; therefore a wideband excitation source covering higher frequencies (i.e. above 1MHz) is required. The main objective of this research is to establish a feasible bandwidth envelope that can be used to design a constant EIM voltage source over a wide bandwidth with low output impedance for practical implementation. An excitation source is one of the major components in bio-impedance measurement systems. In any bio-impedance measurement system the excitation source can be achieved either by injecting current and measuring the resulting voltages, or by applying voltages and measuring the current developed. This paper describes three voltage source architectures and based on their bandwidth comparison; a differential voltage controlled voltage source (VCVS) is proposed, which can be used over a wide bandwidth (>15MHz). This paper describes the performance of the designed EIM voltage source for different load conditions and load capacitances reporting signal-to-noise ratio of approx 90dB at 10MHz frequency, signal phase and maximum of 4.75kΩ source output impedance at 10MHz. Optimum data obtained using Pspice® is used to demonstrate the high-bandwidth performance of the source.

Depth from structured defocus that is independent of the object reflectivity function.

Depth from defocus using structured light is a useful optical metrology technique since the camera and projector can be placed on the same optical axis and it can cope with depth discontinuities. However, the technique can suffer from large errors when used on surfaces with differing reflective properties. This paper demonstrates a method for overcoming this problem.

Heterogeneity of focal breast lesions and surrounding tissue assessed by mammographic texture analysis: preliminary evidence of an association with tumor invasion and estrogen receptor status.

AIM: This pilot study investigates whether heterogeneity in focal breast lesions and surrounding tissue assessed on mammography is potentially related to cancer invasion and hormone receptor status. MATERIALS AND METHODS: Texture analysis (TA) assessed the heterogeneity of focal lesions and their surrounding tissues in digitized mammograms from 11 patients randomly selected from an imaging archive [ductal carcinoma in situ (DCIS) only, n = 4; invasive carcinoma (IC) with DCIS, n = 3; IC only, n = 4]. TA utilized band-pass image filtration to highlight image features at different spatial frequencies (filter values: 1.0-2.5) from fine to coarse texture. The distribution of features in the derived images was quantified using uniformity. RESULTS: Significant differences in uniformity were observed between patient groups for all filter values. With medium scale filtration (filter value = 1.5) pure DCIS was more uniform (median = 0.281) than either DCIS with IC (median = 0.246, p = 0.0102) or IC (median = 0.249, p = 0.0021). Lesions with high levels of estrogen receptor expression were more uniform, most notably with coarse filtration (filter values 2.0 and 2.5, r(s) = 0.812, p = 0.002). Comparison of uniformity values in focal lesions and surrounding tissue showed significant differences between DCIS with or without IC versus IC (p = 0.0009). CONCLUSION: This pilot study shows the potential for computer-based assessments of heterogeneity within focal mammographic lesions and surrounding tissue to identify adverse pathological features in mammographic lesions. The technique warrants further investigation as a possible adjunct to existing computer aided diagnosis systems.

Dynamic contrast-enhanced texture analysis of the liver: initial assessment in colorectal cancer.

PURPOSE: To undertake an initial assessment of the potential utility of dynamic contrast-enhanced texture analysis (DCE-TA) of the liver in patients with colorectal cancer. MATERIALS AND METHODS: TA comprised measurement of mean gray-level intensity, entropy, and uniformity with and without selective-scale filtration using a band-pass filter to highlight different spatial frequencies reflecting fine, medium, and coarse textures. An initial phantom study assessed the sensitivity of each texture qualifier to computed tomography (CT) acquisition parameters. Texture was analyzed in DCE-CT series from 27 colorectal cancer patients having apparently normal hepatic morphology (node-negative: n = 8, node-positive: n = 19). Averaged changes in hepatic texture induced by contrast material were assessed qualitatively and quantitatively by using kinetic modeling to calculate hepatic perfusion indices following fine, medium, and coarse image filtration. RESULTS: All texture qualifiers were less sensitive to changes in CT acquisition parameters than measurement of CT attenuation. Temporal changes in hepatic texture were qualitatively different from changes in enhancement. Statistically significant differences between node-negative and node-positive patients were observed for at least 1 time period for measurements of hepatic enhancement and for all texture parameters. The differences were most statistically significant and occurred over the greatest number of time periods for fine texture quantified as mean gray-level intensity (5 time periods, minimum P value: 0.006) followed by fine texture quantified as entropy (4 time points, minimum P value: 0.006). There was no difference in hepatic perfusion indices for the 2 groups. CONCLUSIONS: DCE-TA is a potentially useful adjunct to DCE-CT warranting further investigation.

Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver.

OBJECTIVES: To determine whether texture analysis of non-contrast enhanced computed tomography (CT) images in apparently disease-free areas of the liver is altered by the presence of extra- and intra-hepatic malignancy in colorectal cancer patients. MATERIALS AND METHODS: Hepatic attenuation and texture were assessed from non-contrast enhanced CT in three groups of colorectal cancer patients: (A) 15 controls with no malignancy; (B) nine patients with extra-hepatic malignancy but no liver involvement; (C) eight patients with hepatic metastases. Regions of interest were manually constructed only over apparently normal areas of liver tissue excluding major blood vessels and areas of intra-hepatic fat, which may otherwise alter CT texture irrespective of the presence of malignancy. Texture was analysed on unfiltered images and following band-pass image filtration to highlight image features at different spatial frequencies (fine: 2 pixels/1.68 mm in width, medium: 6 pixels/5.04 mm and coarse: 12 pixels/10.08 mm). The relative contributions made to the image by features at two different spatial frequencies were expressed as filter ratios (fine/medium, fine/coarse and medium/coarse). Texture was quantified as mean grey-level intensity, entropy and uniformity. RESULTS: Texture was not altered on unfiltered images whereas relative texture analysis following image filtration identified differences in fine to medium texture ratios in apparently disease-free areas of the liver in patients with hepatic metastases as compared to patients with no tumour (entropy, p=0.0257) and patients with extra-hepatic disease (uniformity, p=0.0143). CONCLUSIONS: Relative texture analysis of unenhanced hepatic CT can reveal changes in apparently disease-free areas of the liver that have previously required more complex perfusion measurements for detection.

Performance assessment of the modified-hybrid optical neural network filter.

We present in detail the recorded results of the modified-hybrid optical neural network (M-HONN) filter during a full series of tests to examine its robustness and overall performance for object recognition tasks. We test the M-HONN filter for its detectability and peak sharpness with within-class distortion of the input object, its discrimination ability between an in-class and out-of-class object, and its performance with cluttered images of the true-class object. The M-HONN filter is found to exhibit good detectability, an ability to maintain its correlation-peak sharpness throughout the recorded tests, good discrimination ability, and an ability to detect the true-class object within cluttered input images. Additionally we observe the M-HONN filter's performance within the tests in comparison with the constrained-hybrid optical neural network filter for the first three series of tests and the synthetic discriminant function-maximum average correlation height filter for the fourth set of tests.

Three-dimensional selective-scale texture analysis of computed tomography pulmonary angiograms.

OBJECTIVES: This feasibility study aims to develop 3-dimensional (3D) selective-scale texture analysis of computed tomography pulmonary angiography to identify texture correlates for ventilated and vascular lung for visual and quantitative assessment of pulmonary disorders with altered vasculature. MATERIALS AND METHODS: Computed tomography pulmonary angiography examinations of 8 patients were considered in this study; 3 had normal lungs, 3 had pulmonary embolism (PE1, PE2, and PE3), 1 had only emphysema (PEmp), whereas the final patient had both emphysema and embolism (PEE). Before texture analysis, an initial automated segmentation procedure to include only the lung parenchyma and generation of isometric volume were carried out. From this segmented volume, ventilated lung and pulmonary vessels were separately selected. Texture analysis comprised 2 stages: 1) volume filtration using 3D Laplacian of Gaussian filter to highlight fine and coarse textures within ventilated and vascular lung, followed by 2) quantification of texture using mean gray-level intensity, entropy and uniformity both globally and at 3 anatomic sections of the lung, ie, anterior, middle, and posterior. Quantification of texture was also performed on the unfiltered computed tomography lung dataset. Volume rendering and image fusion of ventilated and vascular lung texture were employed for visualization. RESULTS: For fine texture quantified as mean gray-level intensity in ventilated lung, a postural gradient compatible with known pulmonary physiology was demonstrated and texture was different in emphysematous lung (PEmp and PEE) when compared with nonemphysematous lung (normals, PE1, PE2, and PE3) consistent with altered ventilation. Coarse texture in vascular lung demonstrated a descending trend in entropy (or ascending trend in uniformity) for normals, followed by embolism only (PE1, PE2, and PE3) and finally for emphysematous lung (PEmp and PEE) suggesting a correlation with degree of vascularity (or perfusion). 3D images of ventilated and vascular lung texture highlighted mismatched and matched defects in patients with pulmonary disorders. CONCLUSIONS: This feasibility study demonstrated that 3D filtered texture analysis can potentially provide correlates for ventilated and vascular lung, which may be useful in the diagnosis of PE in the presence of other causes of altered vascularity.

Hepatic enhancement in colorectal cancer: texture analysis correlates with hepatic hemodynamics and patient survival.

RATIONALE AND OBJECTIVES: Perfusion imaging of the liver has attracted interest as a potential means for earlier detection of hepatic metastases, but the techniques are complex and do not form part of routine imaging protocols. This study assesses whether the hemodynamic status of the liver of patients with colorectal cancer but apparently normal hepatic morphology is reflected by texture features within a single portal-phase contrast enhanced computed tomography (CT) image and correlates texture with overall survival. MATERIALS AND METHODS: Portal-phase CT images from 27 patients with colorectal cancer but no apparent hepatic metastases were processed using a band-pass filter that highlighted image features at different spatial frequencies. A range of parameters reflecting liver texture on filtered images were correlated against CT hepatic perfusion index (HPI) and patient survival. RESULTS: After image filtration, entropy values from hepatic regions were inversely correlated with HPI (r=-0.503978, P=.007355), and directly correlated with survival (r=0.489642, P=.009533). An entropy value below 2.0 identified four patients who died within 36 months of their CT scan with sensitivity 100% and specificity 65% (P<.03). CONCLUSION: The hemodynamic status of the liver is reflected by subtle changes in coarse texture on portal phase images that can be revealed by texture analysis. Texture analysis has the potential to identify colorectal cancer patients with an apparently normal portal phase hepatic CT but reduced survival.

In search of biologic correlates for liver texture on portal-phase CT.

RATIONALE AND OBJECTIVES: The acceptance of computer-assisted diagnosis (CAD) in clinical practice has been constrained by the scarcity of identifiable biologic correlates for CAD-based image parameters. This study aims to identify biologic correlates for computed tomography (CT) liver texture in a series of patients with colorectal cancer. MATERIALS AND METHODS: In 28 patients with colorectal cancer, total hepatic perfusion (THP), hepatic arterial perfusion, and hepatic portal perfusion (HPP) were measured using perfusion CT. Hepatic glucose use was also determined from positron emission tomography (PET) and expressed as standardized uptake value (SUV). A hepatic phosphorylation fraction index (HPFI) was determined from both SUV and THP. These physiologic parameters were correlated with CAD parameters namely hepatic densitometry, selective-scale, and relative-scale texture features in apparently normal areas of portal-phase hepatic CT. RESULTS: For patients without liver metastases, a relative-scale texture parameter correlated inversely with SUV (r = -0.587, P = .007) and, positively with THP (r = 0.512, P = .021) and HPP (r = 0.451, P = .046). However, this relative texture parameter correlated most significantly with HPFI (r = -0.590, P = .006). For patients with liver metastases, although not significant an opposite trend was observed between these physiologic parameters and relative texture features (THP: r < -0.4, HPFI: r > 0.35). CONCLUSION: Total hepatic blood flow and glucose metabolism are two distinct but related biologic correlates for liver texture on portal phase CT, providing a rationale for the use of hepatic texture analysis as a indicator for patients with colorectal cancer.

Markovian and autoregressive clutter-noise models for a pattern-recognition Wiener filter.

Most modem pattern recognition filters used in target detection require a clutter-noise estimate to perform efficiently in realistic situations. Markovian and autoregressive models are proposed as an alternative to the white-noise model that has so far been the most widely used. Simulations by use of the Wiener filter and involving real clutter scenes show that both the Markovian and the autoregressive models perform considerably better than the white-noise model. The results also show that both models are general enough to yield similar results with different types of real scenes.