Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Cognitive MAC protocols for mobile Ad-Hoc networks

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The term of Cognitive Radio (CR) used to indicate that spectrum radio could be accessed dynamically and opportunistically by unlicensed users. In CR Networks, Interference between nodes, hidden terminal problem, and spectrum sensing errors are big issues to be widely discussed in the research field nowadays. To improve the performance of such kind of networks, this thesis proposes Cognitive Medium Access Control (MAC) protocols for Mobile Ad-Hoc Networks (MANETs). From the concept of CR, this thesis has been able to develop a cognitive MAC framework in which a cognitive process consisting of cognitive elements is considered, which can make efficient decisions to optimise the CR network. In this context, three different scenarios to maximize the secondary user's throughput have been proposed. We found that the throughput improvement depends on the transition probabilities. However, considering the past information state of the spectrum can dramatically increases the secondary user's throughput by up to 40%. Moreover, by increasing the number of channels, the throughput of the network can be improved about 25%. Furthermore, to study the impact of Physical (PHY) Layer errors on cognitive MAC layer in MANETs, in this thesis, a Sensing Error-Aware MAC protocols for MANETs has been proposed. The developed model has been able to improve the MAC layer performance under the challenge of sensing errors. In this context, the proposed model examined two sensing error probabilities: the false alarm probability and the missed detection probability. The simulation results have shown that both probabilities could be adapted to maintain the false alarm probability at certain values to achieve good results. Finally, in this thesis, a cooperative sensing scheme with interference mitigation for Cognitive Wireless Mesh Networks (CogMesh) has been proposed. Moreover, a prioritybased traffic scenario to analyze the problem of packet delay and a novel technique for dynamic channel allocation in CogMesh is presented. Considering each channel in the system as a sub-server, the average delay of the users' packets is reduced and the cooperative sensing scenario dramatically increases the network throughput 50% more as the number of arrival rate is increased

Study of Strategies for Genetic Variant Discrimination and Detection by Optosensing

Tesis por compendio[ES] La medicina actual se dirige hacia un enfoque más personalizado basándose en el diagnóstico molecular del paciente a través del estudio de biomarcadores específicos. Aplicando este principio molecular, el diagnóstico, pronóstico y selección de la terapia se apoyan en la identificación de variaciones específicas del genoma humano, como variaciones de un único nucleótido (SNV). Para detectar estos biomarcadores se dispone de una amplia oferta de tecnologías. Sin embargo, muchos de los métodos en uso presentan limitaciones como un elevado coste, complejidad, tiempos de análisis largos o requieren de personal y equipamiento especializado, lo que imposibilita su incorporación masiva en la mayoría de los sistemas sanitarios. Por tanto, existe la necesidad de investigar y desarrollar soluciones analíticas que aporten información sobre las variantes genéticas y que se puedan implementar en diferentes escenarios del ámbito de la salud con prestaciones competitivas y económicamente viables. El objetivo principal de esta tesis ha sido desarrollar estrategias innovadoras para resolver el reto de la detección múltiple de variantes genéticas que se encuentran en forma minoritaria en muestras biológicas de pacientes, cubriendo las demandas asociadas al entorno clínico. Las tareas de investigación se centraron en la combinación de reacciones de discriminación alélica con amplificación selectiva de DNA y el desarrollo de sistemas ópticos de detección versátiles. Con el fin de atender el amplio abanico de necesidades, en el primer capítulo, se presentan resultados que mejoran las prestaciones analíticas de la reacción en cadena de la polimerasa (PCR) mediante la incorporación de una etapa al termociclado y de un agente bloqueante amplificando selectivamente las variantes minoritarias que fueron monitorizadas mediante fluorescencia a tiempo real. En el segundo capítulo, se logró la discriminación alélica combinando la ligación de oligonucleótidos con la amplificación de la recombinasa polimerasa (RPA), que al operar a temperatura constante permitió una detección tipo point-of-care (POC). La identificación de SNV se llevó a cabo mediante hibridación en formato micromatriz, utilizando la tecnología Blu-Ray como plataforma de ensayo y detección. En el tercer capítulo, se integró la RPA con la reacción de hibridación alelo especifica en cadena (AS-HCR), en formato array para genotipar SNV a partir de DNA genómico en un chip. La lectura de los resultados se realizó mediante un smartphone. En el último capítulo, se presenta la síntesis de un nuevo reactivo bioluminiscente que se aplicó a la monitorización de biomarcadores de DNA a tiempo real y final de la RPA basada en la transferencia de energía de resonancia de bioluminiscencia (BRET), eliminando la necesidad de una fuente de excitación. Todas las estrategias permitieron un reconocimiento especifico de la variante de interés, incluso en muestras que contenían tan solo 20 copias de DNA genómico diana. Se consiguieron resultados sensibles (límite de detección 0.5% variante/total), reproducibles (desviación estándar relativa < 19%), de manera sencilla (3 etapas o menos), rápida (tiempos cortos de 30-200 min) y permitiendo el análisis simultaneo de varios genes. Como prueba de concepto, estas estrategias se aplicaron a la detección e identificación en muestras clínicas de biomarcadores asociados a cáncer colorrectal y enfermedades cardiológicas. Los resultados se validaron por comparación con los métodos de referencia NGS y PCR, comprobándose que se mejoraban los requerimientos técnicos y la relación coste-eficacia. En conclusión, las investigaciones llevadas a cabo posibilitaron desarrollar herramientas de genotipado con propiedades analíticas competitivas y versátiles, aplicables a diferentes escenarios sanitarios, desde hospitales a entornos con pocos recursos. Estos resultados son prometedores al dar respuesta a la demanda de tecnologías alternativas para el diagnóstico molecular personalizado.[CA] La medicina actual es dirigeix cap a un enfocament més personalitzat basant-se en el diagnòstic molecular del pacient a través de l'estudi de biomarcadors específics. Aplicant aquest principi molecular, el diagnòstic, pronòstic i selecció de la teràpia es recolzen en la identificació de variacions específiques del genoma humà, com variacions d'un únic nucleòtid (SNV). Per a detectar aquests biomarcadors, es disposa d'una àmplia oferta de tecnologies. No obstant això, molts dels mètodes en ús presenten limitacions com un elevat cost, complexitat, temps d'anàlisis llargues o requereixen de personal i equipament especialitzat, la qual cosa impossibilita la seua incorporació massiva en la majoria dels sistemes sanitaris. Per tant, existeix la necessitat d'investigar i desenvolupar solucions analítiques que aporten informació sobre les variants genètiques i que es puguen implementar en diferents escenaris de l'àmbit de la salut amb prestacions competitives i econòmicament viables. L'objectiu principal d'aquesta tesi ha sigut desenvolupar estratègies innovadores per a resoldre el repte de la detecció múltiple de variants genètiques que es troben en forma minoritària en mostres biològiques de pacients, cobrint les demandes associades a l'entorn clínic. Les tasques d'investigació es van centrar en la combinació de reaccions de discriminació al·lèlica amb amplificació selectiva de DNA i al desenvolupament de sistemes òptics de detecció versàtils. Amb la finalitat d'atendre l'ampli ventall de necessitats, en el primer capítol, es presenten resultats que milloren les prestacions analítiques de la reacció en cadena de la polimerasa (PCR) mitjançant la incorporació d'una etapa al termociclat i d'un agent bloquejant amplificant selectivament les variants minoritàries que van ser monitoritzades mitjançant fluorescència a temps real. En el segon capítol, es va aconseguir la discriminació al·lèlica combinant el lligament d'oligonucleòtids amb l'amplificació de la recombinasa polimerasa (RPA), que en operar a temperatura constant va permetre una detecció tipus point-of-care (POC). La identificació de SNV es va dur a terme mitjançant hibridació en format micromatriu, utilitzant la tecnologia Blu-Ray com a plataforma d'assaig i detecció. En el tercer capítol, es va integrar la RPA amb la reacció d'hibridació al·lel específica en cadena (AS-HCR), en format matriu per a genotipar SNV a partir de DNA genòmic en un xip. La lectura dels resultats es va realitzar mitjançant un telèfon intel·ligent. En l'últim capítol, es presenta la síntesi d'un nou reactiu bioluminescent que es va aplicar al monitoratge de biomarcadors de DNA a temps real i final de la RPA basada en la transferència d'energia de ressonància de bioluminescència (BRET), eliminant la necessitat d'una font d'excitació. Totes les estratègies van permetre un reconeixement específic de la variant d'interès, fins i tot en mostres que només contenien 20 còpies de DNA genòmic diana. Es van aconseguir resultats sensibles (límit de detecció 0.5% variant/total), reproduïbles (desviació estàndard relativa < 19%), de manera senzilla (3 etapes o menys), ràpida (temps curts de 30-200 min) i permetent l'anàlisi simultània de diversos gens. Com a prova de concepte, aquestes estratègies es van aplicar a la detecció i identificació en mostres clíniques de biomarcadors associats a càncer colorectal i a malalties cardiològiques. Els resultats es van validar per comparació amb els mètodes de referència NGS i PCR, comprovant-se que es milloraven els requeriments tècnics i la relació cost-eficàcia. En conclusió, les investigacions dutes a terme van possibilitar desenvolupar eines de genotipat amb propietats analítiques competitives i versàtils, aplicables a diferents escenaris sanitaris, des d'hospitals a entorns amb pocs recursos. Aquests resultats són prometedors en donar resposta a la demanda de tecnologies alternatives per al diagnòstic molecular personalitzat.[EN] Current medicine is moving towards a more personalized approach based on the patients' molecular diagnosis through the study of specific biomarkers. Diagnosis, prognosis and therapy selection, applying this molecular principle, rely on identifying specific variations in the human genome, such as single nucleotide variations (SNV). A wide range of technologies is available to detect these biomarkers. However, many of the employed methods have limitations such as high cost, complexity, long analysis times, or requiring specialized personnel and equipment, making their massive incorporation in most healthcare systems impossible. Therefore, there is a need to research and develop analytical solutions that provide information on genetic variants that can be implemented in different health scenarios with competitive and economically feasible performances. The main objective of this thesis has been to develop innovative strategies to solve the challenge of multiple detection of genetic variants that are found in a minority amount in patient samples, covering the demands associated with the clinical setting. Research tasks focused on the combination of allelic discrimination reactions with selective DNA amplification and the development of versatile optical detection systems. In order to meet the wide range of needs, in the first chapter, the analytical performances of the polymerase chain reaction (PCR) were improved by incorporating a thermocycling step and a blocking agent to amplify selectively minority variants that were monitored by real-time fluorescence. In the second chapter, allelic discrimination was achieved by combining oligonucleotide ligation with recombinase polymerase amplification (RPA), which operates at a constant temperature, allowing point-of-care (POC) detection. SNV identification was carried out by hybridization in microarray format, using Blu-Ray technology as the assay platform and detector. RPA was integrated with allele-specific hybridization chain reaction (AS-HCR), in an array format to genotype SNV from genomic DNA on a chip in the third chapter. The reading of the results was performed using a smartphone. In the last chapter, a new bioluminescent reagent was synthesized. It was applied to real-time and endpoint DNA biomarker monitoring based on bioluminescence resonance energy transfer (BRET), eliminating the need for an excitation source. All the strategies allowed specific recognition of the target variant, even in samples containing as few as 20 copies of target genomic DNA. Sensitive (limit of detection 0.5% variant/total), reproducible (relative standard deviation < 19%), simple (3 steps or less), fast (short times of 30-200 min) results were achieved, allowing simultaneous analysis of several genes. As proof of concept, these strategies were applied to detect and identify biomarkers associated with colorectal cancer and cardiological diseases in clinical samples. The results were validated by comparison with reference methods such as NGS and PCR, proving that the technical requirements and cost-effectiveness were improved. In conclusion, the developed research made it possible to develop genotyping tools with competitive analytical properties and versatile, applicable to different healthcare scenarios, from hospitals to limited-resource environments. These results are promising since they respond to the demand for alternative technologies for personalized molecular diagnostics.The authors acknowledge the financial support received from the Generalitat Valenciana PROMETEO/2020/094, GRISOLIA/2014/024 PhD Grant and GVA-FPI-2017 PhD grant, the Spanish Ministry of Economy and Competitiveness MINECO projects CTQ2016-75749-R and PID2019-110713RB-I00 and European Regional Development Fund (ERDF).Lázaro Zaragozá, A. (2022). Study of Strategies for Genetic Variant Discrimination and Detection by Optosensing [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185216TESISCompendi

Simulation and implementation of novel deep learning hardware architectures for resource constrained devices

Corey Lammie designed mixed signal memristive-complementary metal–oxide–semiconductor (CMOS) and field programmable gate arrays (FPGA) hardware architectures, which were used to reduce the power and resource requirements of Deep Learning (DL) systems; both during inference and training. Disruptive design methodologies, such as those explored in this thesis, can be used to facilitate the design of next-generation DL systems

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

D4.3 Final Report on Network-Level Solutions

Research activities in METIS reported in this document focus on proposing solutions to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond. This document provides the final findings on several network-level aspects and groups of solutions that are considered essential for designing future 5G solutions. Specifically, it elaborates on: -Interference management and resource allocation schemes -Mobility management and robustness enhancements -Context aware approaches -D2D and V2X mechanisms -Technology components focused on clustering -Dynamic reconfiguration enablers These novel network-level technology concepts are evaluated against requirements defined by METIS for future 5G systems. Moreover, functional enablers which can support the solutions mentioned aboveare proposed. We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

Smart PIN: performance and cost-oriented context-aware personal information network

The next generation of networks will involve interconnection of heterogeneous individual networks such as WPAN, WLAN, WMAN and Cellular network, adopting the IP as common infrastructural protocol and providing virtually always-connected network. Furthermore, there are many devices which enable easy acquisition and storage of information as pictures, movies, emails, etc. Therefore, the information overload and divergent content’s characteristics make it difficult for users to handle their data in manual way. Consequently, there is a need for personalised automatic services which would enable data exchange across heterogeneous network and devices. To support these personalised services, user centric approaches for data delivery across the heterogeneous network are also required. In this context, this thesis proposes Smart PIN - a novel performance and cost-oriented context-aware Personal Information Network. Smart PIN's architecture is detailed including its network, service and management components. Within the service component, two novel schemes for efficient delivery of context and content data are proposed: Multimedia Data Replication Scheme (MDRS) and Quality-oriented Algorithm for Multiple-source Multimedia Delivery (QAMMD). MDRS supports efficient data accessibility among distributed devices using data replication which is based on a utility function and a minimum data set. QAMMD employs a buffer underflow avoidance scheme for streaming, which achieves high multimedia quality without content adaptation to network conditions. Simulation models for MDRS and QAMMD were built which are based on various heterogeneous network scenarios. Additionally a multiple-source streaming based on QAMMS was implemented as a prototype and tested in an emulated network environment. Comparative tests show that MDRS and QAMMD perform significantly better than other approaches

Polymer Microsystems for the Enrichment of Circulating Tumor Cells and their Clinical Demonstration

Cancer research is centered on the discovery of new biomarkers that could unlock the obscurities behind the mechanisms that cause cancer or those associated with its spread (i.e., metastatic disease). Circulating tumor cells (CTCs) have emerged as attractive biomarkers for the management of many cancer-related diseases due primarily to the ease of securing them from a simple blood draw. However, their rarity (~1 CTC per mL of whole blood) makes enrichment analytically challenging. Microfluidic systems are viewed as exquisite platforms for the clinical analysis of CTCs due to their ability to be used in an automated fashion, minimizing sample loss and contamination. This has formed the basis of the reported research, which focused on the development of microfluidic systems for CTC analysis. The system reported herein consisted of a modular design and targeted the analysis of CTCs using pancreatic ductal adenocarcinoma (PDAC) as the model disease for determining the utility of the system. The system was composed of 3 functional modules; (i) a thermoplastic CTC selection module consisting of high aspect ratio (30 µm x 150 µm) channels; (ii) an impedance sensor module for label-less CTC counting; and (iii) a staining and imaging module for phenotype identification of selected CTCs. The system could exhaustively process 7.5 mL of blood in \u3c45 min with CTC recoveries \u3e90% directly from whole blood. In addition, significantly reduced assay turnaround times (8 h to 1.5 h) was demonstrated. We also show the ability to detect KRAS gene mutations from CTCs enriched by the microfluidic system. As a proof-of-concept, the ability to identify KRAS point mutations using a PCR/LDR/CE assay from as low as 10 CTCs enriched by the integrated microfluidic system was demonstrated. Finally, the clinical utility of the polymer-based microfluidic device for the analysis of circulating multiple myeloma cells (CMMCs) was demonstrated as well. Parameters such as translational velocity and recovery of CMMCs were optimized and found to be 1.1 mm/s and 71%, respectively. Also demonstrated was on-chip immunophenotyping and clonal testing of CMMCs, which has been reported to be prognostically significant. Further, a pilot study involving 26 patients was performed using the polymer microfluidic device with the aim of correlating the number of CMMCs with disease activity. An average of 347 CMMCs/mL of whole blood was recovered from blood volumes of approximately 0.5 mL