Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging

Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

Imaging of the human fundus in the clinical setting:past present and future

The human fundus is a complex structure that can be easily visualized and the world of ophthalmology is going through a golden era of new and exciting fundus imaging techniques; recent advances in technology have allowed a significant improvement in the imaging modalities clinicians have available to formulate a diagnostic and treatment plan for the patient, but there is constant on-going work to improve current technology and create new ideas in order to gather as much information as possible from the human fundus. In this article we shall summarize the imaging techniques available in the standard medical retina clinic (i.e. not limited to the research lab) and delineate the technologies that we believe will have a significant impact on the way clinicians will assess retinal and choroidal pathology in the not too distant future.

25th RCOphth Congress, President's Session paper:25 years of progress in medical retina

The quarter century since the foundation of the Royal College of Ophthalmologists has coincided with immense change in the subspecialty of medical retina, which has moved from being the province of a few dedicated enthusiasts to being an integral, core part of ophthalmology in every eye department. In age-related macular degeneration, there has been a move away from targeted, destructive laser therapy, dependent on fluorescein angiography to intravitreal injection therapy of anti-growth factor agents, largely guided by optical coherence tomography. As a result of these changes, ophthalmologists have witnessed a marked improvement in visual outcomes for their patients with wet age-related macular degeneration (AMD), while at the same time developing and enacting entirely novel ways of delivering care. In the field of diabetic retinopathy, this period also saw advances in laser technology and a move away from highly destructive laser photocoagulation treatment to gentler retinal laser treatments. The introduction of intravitreal therapies, both steroids and anti-growth factor agents, has further advanced the treatment of diabetic macular oedema. This era has also seen in the United Kingdom the introduction of a coordinated national diabetic retinopathy screening programme, which offers an increasing hope that the burden of blindness from diabetic eye disease can be lessened. Exciting future advances in retinal imaging, genetics, and pharmacology will allow us to further improve outcomes for our patients and for ophthalmologists specialising in medical retina, the future looks very exciting but increasingly busy.

Image Sensors in Security and Medical Applications

This paper briefly reviews CMOS image sensor technology and its utilization in security and medical applications. The role and future trends of image sensors in each of the applications are discussed. To provide the reader deeper understanding of the technology aspects the paper concentrates on the selected applications such as surveillance, biometrics, capsule endoscopy and artificial retina. The reasons for concentrating on these applications are due to their importance in our daily life and because they present leading-edge applications for imaging systems research and development. In addition, review of image sensors implementation in these applications allows the reader to investigate image sensor technology from the technical and from other views as well.

Rigid and non-rigid point-based medical image registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Rigid and Non-rigid Point-based Medical Image Registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Improving magnetic resonance imaging (MRI) examinations : Development and evaluation of an intervention to reduce movement in scanners and facilitate scan completion

© 2015 The British Psychological Society.

Improving magnetic resonance imaging (MRI) examinations : Development and evaluation of an intervention to reduce movement in scanners and facilitate scan completion

© 2015 The British Psychological Society.

Longitudinal diffusion tensor imaging in dementia with Lewy bodies and Alzheimer's disease

Copyright © 2016 Elsevier Ltd. All rights reserved. Acknowledgements The study was supported by the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge, and the NIHR Biomedical Research Unit in Dementia and the Biomedical Research Centre awarded to Newcastle upon Tyne Hospitals NHS Foundation Trust and Newcastle University. Elijah Mak was in receipt of a Gates Cambridge PhD studentship.

Whole-brain patterns of 1H-magnetic resonance spectroscopy imaging in Alzheimer's disease and dementia with Lewy bodies

Acknowledgments We thank Craig Lambert for his help in processing the MRS data. The study was funded by the Sir Jules Thorn Charitable Trust (grant ref: 05/JTA) and was supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre and the Biomedical Research Unit in Lewy Body Dementia based at Newcastle upon Tyne Hospitals National Health Service (NHS) Foundation Trust and Newcastle University and the NIHR Biomedical Research Centre and Biomedical Research Unit in Dementia based at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

Proposing the deep dynamic Bayesian network as a future computer based medical system

The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.

Imaging in non Traumatic Emergencies: Acute Thrombosis of the Aorta and Pulmonary Embolism

Objectives: To present the possibility of acute arterial and venous thrombosis. Materials and methods: Report of a patient presenting with acute dyspnoea and chest pain. Results: Using a combined medical team and imaging studies, pulmonary embolism and acute arterial thrombosis were diagnosed. The patient was treated medically and surgically. Conclusion: Physicians should be aware of the possibility of combined thrombosis and the diagnosis and management of the condition.