Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

We propose a novel attention gate (AG) model for medical image analysis that automatically learns to focus on target structures of varying shapes and sizes. Models trained with AGs implicitly learn to suppress irrelevant regions in an input image while highlighting salient features useful for a specific task. This enables us to eliminate the necessity of using explicit external tissue/organ localisation modules when using convolutional neural networks (CNNs). AGs can be easily integrated into standard CNN models such as VGG or U-Net architectures with minimal computational overhead while increasing the model sensitivity and prediction accuracy. The proposed AG models are evaluated on a variety of tasks, including medical image classification and segmentation. For classification, we demonstrate the use case of AGs in scan plane detection for fetal ultrasound screening. We show that the proposed attention mechanism can provide efficient object localisation while improving the overall prediction performance by reducing false positives. For segmentation, the proposed architecture is evaluated on two large 3D CT abdominal datasets with manual annotations for multiple organs. Experimental results show that AG models consistently improve the prediction performance of the base architectures across different datasets and training sizes while preserving computational efficiency. Moreover, AGs guide the model activations to be focused around salient regions, which provides better insights into how model predictions are made. The source code for the proposed AG models is publicly available.Comment: Accepted for Medical Image Analysis (Special Issue on Medical Imaging with Deep Learning). arXiv admin note: substantial text overlap with arXiv:1804.03999, arXiv:1804.0533

Clinical reasoning in canine spinal disease: what combination of clinical information is useful?

Spinal disease in dogs is commonly encountered in veterinary practice. Numerous diseases may cause similar clinical signs and presenting histories. The study objective was to use statistical models to identify combinations of discrete parameters from the patient signalment, history and neurological examination that could suggest the most likely diagnoses with statistical significance. A retrospective study of 500 dogs referred to the Queen Mother Hospital for Animals before June 2012 for the investigation of spinal disease was performed. Details regarding signalment, history, physical and neurological examinations, neuroanatomical localisation and imaging data were obtained. Univariate analyses of variables (breed, age, weight, onset, deterioration, pain, asymmetry, neuroanatomical localisation) were performed, and variables were retained in a multivariate logistic regression model if P<0.05. Leading diagnoses were intervertebral disc extrusion (IVDE, n=149), intervertebral disc protrusion (n=149), ischaemic myelopathy (IM, n=48) and neoplasms (n=44). Multivariate logistic regression characterised IM and acute non-compressive nucleus pulposus extrusions as the only peracute onset, non-progressive, non-painful and asymmetrical T3-L3 myelopathies. IVDE was most commonly characterised as acute onset, often deteriorating, painful and largely symmetrical T3-L3 myelopathy. This study suggests that most spinal diseases cause distinctive combinations of presenting clinical parameters (signalment, onset, deterioration, pain, asymmetry, neuroanatomical localisation). Taking particular account of these parameters may aid decision making in a clinical setting

Multimodal localisation : analysis, algorithms and experimental evaluation

The term localisation is derived from the word locale, which traditionally means a small area or vicinity. In ancient days, localisation meant navigation -- an art of finding the way from one place to another. Tremendous advancement in the science of navigation dates back to the sixteenth century, when instruments like compasses, sextants and the first ever clock to keep the time exactly were devised. Advancement in navigation brought ways and means to explore the world, be it for expansion of the territories or for promoting trade and business. Since then localisation has been explored for several decades as a classical problem in many disciplines -- including robotics, virtual reality, navigation. Now we are in the era of ubiquitous computing -- a term coined by the visionary Mark Weiser in the early 1990s. Weiser sees technology only as a means to an end, which should take a back seat in order to allow user to fully concentrate on the task at hand. Looking from a technological standpoint, today we are surrounded by a wealth of devices enriched with sensing, computing and communication capabilities which are seamlessly integrated in our daily lives. Knowing the location of an object is an important cornerstone and fertile research area in ubiquitous computing. \ud \ud \ud The growing need of location systems underscores the\ud importance of addressing this problem -- government initiatives to locate emergency call by cellular network providers and the increasing usage of global positioning systems (GPS) in many commercial applications as in navigation are just a few examples. Since the field is active and vibrant, new services and market players are constantly emerging. Google have just launched a new service called Latitude, which lets smart phone and laptop users share their location with friends and allows those friends to share their locations in return. Latitude uses satellites and cell towers to estimate location. The market for GPS products and services alone is expected to grow to USD200 billion by 2015. Real-time location systems (RTLS) in the transport and logistics sector drive the penetration of several location-based solutions. The number of RTLS suppliers is expected to increase from 50 to 200 by 2013, reflecting a market growth from USD 145 million in 2008 to USD 2.7 billion in 2013. Despite the extraordinary advances in outdoor localisation and navigation, indoor localisation still remains an open challenge.\ud \ud Fundamental to any location system are the algorithms used to estimate location. This thesis focuses on formulation of localisation algorithms with the capability of fusing measurements from multiple modalities. We begin by systematically analysing the basic principles of localisation through a review and classification of the state of the art. From our detailed survey, it is evident that no location system is error-free and suited for all situations. For example, pure inertial sensors suffer from drift, ultrasound sensors require clear line of sight and magnetic sensors are affected by ferromagnetic and conductive materials in the environment. Thus, we rationalise "multimodal localisation" as one of the promising ways for improving location accuracy. Apart from improving performance of the location system in limited measurement volumes, fusion of heterogeneous sensing systems will ultimately allow people to move between places covered by different sensing systems without loss of location knowledge.\ud We explore localisation algorithms that use multiple sensing modalities to improve accuracy and robustness. To ground our work, we have chosen three specific applications covering both infrastructure-based positioning and ad hoc-based positioning systems. From our taxonomy, we create a blueprint of location technologies that would meet those three application needs.\ud -Localisation in office environments to facilitate social networking, as a way to help coordination of people and understand social patterns. We leverage the existing wireless local-area networks (WLAN) infrastructure to sense motion and location with the main motivation of building wide-area location services. Our contributions include-- (i) in-depth characterisation of received signal strength (RSSI), (ii) novel algorithms to deduce motion by observing fluctuations in RSSI across all the access points in range, and (iii) performance comparison using real data against common deterministic location algorithms with and without adding motion information.\ud -Transport and logistics operation (e.g. in warehouses), motivating the need of fine-grained location information. We use ultra-wideband (UWB) as it copes with harsh indoor environments better than conventional radio technologies. Our contributions include-- (i) characterisation of heterogeneous observations (pseudoranges and angles) obtained from two deployments, mimicking real-world (low-overhead) vs. ideal deployment (carefully planned and calibrated), (ii) formulation of algorithms to fuse heterogeneous observations and (iii) a thorough evaluation for both static and dynamic tracking.\ud -Emergency response scenarios, motivating the need for ad hoc positioning capabilities. In particular, we use a combination of inertial sensors and ultrasound sensors. The position error in a purely inertial system increases with time and requires correction from external sources. We address this problem by deploying ultrasound sensors as landmarks correcting for the inertial drift. Our contributions include-- (i) characterisation of inertial and ultrasound data, (ii) algorithms to support guidance and tracking and (iii) a thorough evaluation from data gathered from real deployments.\ud While the chosen technologies and applications are not exhaustive, they are representative as they cover a broad spectrum across several dimensions: accuracy -- fine grained to coarse grained, coverage -- room-level to wide-area, dependence -- dense infrastructure to ad hoc, cost -- expensive to minimal cost. In every instance, we have illustrated the benefits of combining multiple modalities.\ud In short, our contributions include algorithms for motion detection and technology independent localisation algorithms that have the ability to fuse readings across different sensing technologies and incorporate motion models to improve accuracy significantly. Another important aspect of the work presented in this thesis is the characterisation of the raw measurement errors of the individual modalities. In all cases, we perform a rigorous evaluation of the presented algorithms by using measurements collected from real deployments. \u

A Low Cost Ultrasound-based Localisation System

This paper presents a low-cost localisation system based on ultrasonic sensing and time of flight measurements. A compact ultrasound emitter has been designed to generate omnidirectional train of ultrasound pulses which are then picked up by several fixed receivers measuring the time difference of arrival. A least squares approach is used to analytically obtain a first estimate of the emitter position, which is then refined through steepest descent optimisation. All processing is done via a standard Arduino platform, proving the low computational demands of the method. Localisation results are validated against a state-of-the-art Optitrack motion capture system. It is shown that the system can cover a 4.3x3.1m arena with a mean error localisation error of 1.57cm and an average standard deviation of 1.39cm throughout the arena

Expression of KOC, S100P, mesothelin and MUC1 in pancreatico-biliary adenocarcinomas: development and utility of a potential diagnostic immunohistochemistry panel

&lt;b&gt;Background&lt;/b&gt; Pancreatico-biliary adenocarcinomas (PBA) have a poor prognosis. Diagnosis is usually achieved by imaging and/or endoscopy with confirmatory cytology. Cytological interpretation can be difficult especially in the setting of chronic pancreatitis/cholangitis. Immunohistochemistry (IHC) biomarkers could act as an adjunct to cytology to improve the diagnosis. Thus, we performed a meta-analysis and selected KOC, S100P, mesothelin and MUC1 for further validation in PBA resection specimens.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methods&lt;/b&gt; Tissue microarrays containing tumour and normal cores in a ratio of 3:2, from 99 surgically resected PBA patients, were used for IHC. IHC was performed on an automated platform using antibodies against KOC, S100P, mesothelin and MUC1. Tissue cores were scored for staining intensity and proportion of tissue stained using a Histoscore method (range, 0–300). Sensitivity and specificity for individual biomarkers, as well as biomarker panels, were determined with different cut-offs for positivity and compared by summary receiver operating characteristic (ROC) curve.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; The expression of all four biomarkers was high in PBA versus normal ducts, with a mean Histoscore of 150 vs. 0.4 for KOC, 165 vs. 0.3 for S100P, 115 vs. 0.5 for mesothelin and 200 vs. 14 for MUC1 (p &lt; .0001 for all comparisons). Five cut-offs were carefully chosen for sensitivity/specificity analysis. Four of these cut-offs, namely 5%, 10% or 20% positive cells and Histoscore 20 were identified using ROC curve analysis and the fifth cut-off was moderate-strong staining intensity. Using 20% positive cells as a cut-off achieved higher sensitivity/specificity values: KOC 84%/100%; S100P 83%/100%; mesothelin 88%/92%; and MUC1 89%/63%. Analysis of a panel of KOC, S100P and mesothelin achieved 100% sensitivity and 99% specificity if at least 2 biomarkers were positive for 10% cut-off; and 100% sensitivity and specificity for 20% cut-off.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusion&lt;/b&gt; A biomarker panel of KOC, S100P and mesothelin with at least 2 biomarkers positive was found to be an optimum panel with both 10% and 20% cut-offs in resection specimens from patients with PBA.&lt;p&gt;&lt;/p&gt

The clinical application of PET/CT: a contemporary review

The combination of positron emission tomography (PET) scanners and x-ray computed tomography (CT) scanners into a single PET/CT scanner has resulted in vast improvements in the diagnosis of disease, particularly in the field of oncology. A decade on from the publication of the details of the first PET/CT scanner, we review the technology and applications of the modality. We examine the design aspects of combining two different imaging types into a single scanner, and the artefacts produced such as attenuation correction, motion and CT truncation artefacts. The article also provides a discussion and literature review of the applications of PET/CT to date, covering detection of tumours, radiotherapy treatment planning, patient management, and applications external to the field of oncology

Update on the ICUD-SIU consultation on multi-parametric magnetic resonance imaging in localised prostate cancer

Introduction: Prostate cancer (PCa) imaging is a rapidly evolving field. Dramatic improvements in prostate MRI during the last decade will probably change the accuracy of diagnosis. This chapter reviews recent current evidence about MRI diagnostic performance and impact on PCa management. Materials and methods: The International Consultation on Urological Diseases nominated a committee to review the literature on prostate MRI. A search of the PubMed database was conducted to identify articles focussed on MP-MRI detection and staging protocols, reporting and scoring systems, the role of MP-MRI in diagnosing PCa prior to biopsy, in active surveillance, in focal therapy and in detecting local recurrence after treatment. Results: Differences in opinion were reported in the use of the strength of magnets [1.5 Tesla (T) vs. 3T] and coils. More agreement was found regarding the choice of pulse sequences; diffusion-weighted MRI (DW-MRI), dynamic contrast-enhanced MRI (DCE MRI), and/or MR spectroscopy imaging (MRSI) are recommended in addition to conventional T2-weighted anatomical sequences. In 2015, the Prostate Imaging Reporting and Data System (PI-RADS version 2) was described to standardize image acquisition and interpretation. MP-MRI improves detection of clinically significant PCa (csPCa) in the repeat biopsy setting or before the confirmatory biopsy in patients considering active surveillance. It is useful to guide focal treatment and to detect local recurrences after treatment. Its role in biopsy-naive patients or during the course of active surveillance remains debated. Conclusion: MP-MRI is increasingly used to improve detection of csPCa and for the selection of a suitable therapeutic approach

Cooperatively Extending the Range of Indoor Localisation

̶Whilst access to location based information has been mostly possible in the\ud outdoor arena through the use of GPS, the provision of accurate positioning estimations and\ud broad coverage in the indoor environment has proven somewhat problematic to deliver.\ud Considering more time is spent in the indoor environment, the requirement for a solution is\ud obvious. The topography of an indoor location with its many walls, doors, pillars, ceilings\ud and floors etc. muffling the signals to \from mobile devices and their tracking devices, is one\ud of the many barriers to implementation. Moreover the cha racteristically noisy behaviour of\ud wireless devices such as Bluetooth headsets, cordless phones and microwaves can cause\ud interference as they all operate in the same band as Wi -Fi devices. The limited range of\ud tracking devices such as Wireless Access Point s (AP), and the restrictions surrounding their\ud positioning within a buildings’ infrastructure further exacerbate this issue, these difficulties\ud provide a fertile research area at present.\ud The genesis for this research is the inability of an indoor location based system (LBS) to\ud locate devices beyond the range of the fixed tracking devices. The hypothesis advocates a\ud solution that extends the range of Indoor LBS using Mobile Devices at the extremities of\ud Cells that have a priori knowledge of their location, and utilizing these devices to ascertain\ud the location of devices beyond the range of the fixed tracking device. This results in a\ud cooperative localisation technique where participating devices come together to aid in the\ud determination of location of device s which otherwise would be out of scope

Determination of optimal ultrasound planes for the initialisation of image registration during endoscopic ultrasound-guided procedures

PURPOSE: Navigation of endoscopic ultrasound (EUS)-guided procedures of the upper gastrointestinal (GI) system can be technically challenging due to the small fields-of-view of ultrasound and optical devices, as well as the anatomical variability and limited number of orienting landmarks during navigation. Co-registration of an EUS device and a pre-procedure 3D image can enhance the ability to navigate. However, the fidelity of this contextual information depends on the accuracy of registration. The purpose of this study was to develop and test the feasibility of a simulation-based planning method for pre-selecting patient-specific EUS-visible anatomical landmark locations to maximise the accuracy and robustness of a feature-based multimodality registration method. METHODS: A registration approach was adopted in which landmarks are registered to anatomical structures segmented from the pre-procedure volume. The predicted target registration errors (TREs) of EUS-CT registration were estimated using simulated visible anatomical landmarks and a Monte Carlo simulation of landmark localisation error. The optimal planes were selected based on the 90th percentile of TREs, which provide a robust and more accurate EUS-CT registration initialisation. The method was evaluated by comparing the accuracy and robustness of registrations initialised using optimised planes versus non-optimised planes using manually segmented CT images and simulated ([Formula: see text]) or retrospective clinical ([Formula: see text]) EUS landmarks. RESULTS: The results show a lower 90th percentile TRE when registration is initialised using the optimised planes compared with a non-optimised initialisation approach (p value [Formula: see text]). CONCLUSIONS: The proposed simulation-based method to find optimised EUS planes and landmarks for EUS-guided procedures may have the potential to improve registration accuracy. Further work will investigate applying the technique in a clinical setting