TPU Cloud-Based Generalized U-Net for Eye Fundus Image Segmentation

Medical images from different clinics are acquired with different instruments and settings. To perform segmentation on these images as a cloud-based service we need to train with multiple datasets to increase the segmentation independency from the source. We also require an ef cient and fast segmentation network. In this work these two problems, which are essential for many practical medical imaging applications, are studied. As a segmentation network, U-Net has been selected. U-Net is a class of deep neural networks which have been shown to be effective for medical image segmentation. Many different U-Net implementations have been proposed.With the recent development of tensor processing units (TPU), the execution times of these algorithms can be drastically reduced. This makes them attractive for cloud services. In this paper, we study, using Google's publicly available colab environment, a generalized fully con gurable Keras U-Net implementation which uses Google TPU processors for training and prediction. As our application problem, we use the segmentation of Optic Disc and Cup, which can be applied to glaucoma detection. To obtain networks with a good performance, independently of the image acquisition source, we combine multiple publicly available datasets (RIM-One V3, DRISHTI and DRIONS). As a result of this study, we have developed a set of functions that allow the implementation of generalized U-Nets adapted to TPU execution and are suitable for cloud-based service implementation.Ministerio de Economía y Competitividad TEC2016-77785-

An eLearning Standard Approach for Supporting PBL in Computer Engineering

Problem-based learning (PBL) has proved to be a highly successful pedagogical model in many fields, although it is not that common in computer engineering. PBL goes beyond the typical teaching methodology by promoting student interaction. This paper presents a PBL trial applied to a course in a computer engineering degree at the University of Seville, Spain. To promote the reusability and interoperability of the PBL trial, a design-driven approach was used, based on the Internet protocol Multimedia Subsystems (IMS) Learning Design (LD) standard. This paper presents the outcomes of using this method to innovate teaching practices in a blended learning environment. Design and implementation results, as well as users' opinions, are presented and analyzed.Ministerio de Educación y Ciencia TIN2006-15617-C03-03Junta de Andalucía P06-TIC-0229

Using virtual potential fields for electric wheelchair guidance

TetraNauta is an electric wheelchair guidance system intended for people with heavy motion impairments (such as persons with tetraplegia). It is specially useful when impairments also affect wheelchair steering as it is able to automatically guide wheelchairs between different points in a known environment (a hospital, a school, etc), conditioned with track marks painted on the floor. It also provides a semiautomatic navigation mode, where control is shared between user and navigation system. It is intended for learning wheelchair manipulation and as an aid in places where navigation is difficult or dangerous (i.e. for crossing narrow corridors)

On the Design of Ambient Intelligent Systems in the Context of Assistive Technologies

The design of Ambient Intelligent Systems (AISs) is discussed in the context of assistive technologies. The main issues include ubiquitous communications, context awareness, natural interactions and heterogeneity, which are analyzed using some examples. A layered architecture is proposed for heterogeneous sub-systems integration with three levels of interactions that may be used as a framework to design assistive AISs.Ministerio de Ciencia y Tecnología TIC2001-1868-C0

A generalization of path following for mobile robots

Several authors have proposed some methods for applying path following in specific cases to mobile robots. When we try to extend the path following approach to the general problem several difficulties arise. We present a generalized technique to apply path following to a mobile robot with nonholonomic constraints. As an application example, we expose the case of mobile robots with a higher degree of manoeuvrability than the typical car-like robots. In particular we consider a robot that can turn around itself making a zero-radius turn; a case still not resolved as far as we know. Finally we propose a suitable control law for this example that ensures asymptotical convergence.Comisión Interministerial de Ciencia y Tecnología TER96-2056-C02-0

Dual Machine-Learning system to aid Glaucoma Diagnosis using disc and cup feature extraction.

Glaucoma is a degenerative disease that affects vision, causing damage to the optic nerve that ends in vision loss. The classic techniques to detect it have undergone a great change since the intrusion of machine learning techniques into the processing of eye fundus images. Several works focus on training a convolutional neural network (CNN) by brute force, while others use segmentation and feature extraction techniques to detect glaucoma. In this work, a diagnostic aid tool to detect glaucoma using eye fundus images is developed, trained and tested. It consists of two subsystems that are independently trained and tested, combining their results to improve glaucoma detection. The first subsystem applies machine learning and segmentation techniques to detect optic disc and cup independently, combine them and extract their physical and positional features. The second one applies transfer learning techniques to a pre-trained CNN to detect glaucoma through the analysis of the complete eye fundus images. The results of both systems are combined to discriminate positive cases of glaucoma and improve final detection. The results show that this system achieves a higher classification rate than previous works. The system also provides information on the basis for the proposed diagnosis suggestion that can help the ophthalmologist to accept or modify it

AER tools for Communications and Debugging

Address-event-representation (AER) is a communications protocol for transferring spikes between bio-inspired chips. Such systems may consist of a hierarchical structure with several chips that transmit spikes among them in real time, while performing some processing. To develop and test AER based systems it is convenient to have a set of instruments that would allow to: generate AER streams, monitor the output produced by neural chips and modify the spike stream produced by an emitting chip to adapt it to the requirements of the receiving elements. In this paper we present a set of tools that implement these functions developed in the CAVIAR EU projectUnión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-0

A Protocol Generator Tool for Automatic In-Vitro HPV Robotic Analysis

Human Papilloma Virus (HPV) could develop precancerous lesions and invasive cancer, as it is the main cause of nearly all cases of cervical cancer. There are many strains of HPV and current vaccines can only protect against some of them. This makes the detection and genotyping of HPV a research area of utmost importance. Several biomedical systems can detect HPV in DNA samples; however, most of them do not have a procedure as fast, automatic or precise as it is actually needed in this field. This manuscript presents a novel XML-based hierarchical protocol architecture for biomedical robots to describe each protocol step and execute it sequentially, along with a robust and automatic robotic system for HPV DNA detection capable of processing from 1 to 24 samples simultaneously in a fast (from 45 to 162 min), efficient (100% markers effectiveness) and precise (able to detect 36 different HPV genotypes) way. It includes an efficient artificial vision process as the last step of the diagnostic.FIDETIA P055-12/E03Ministerio de Economía y Competitivida TEC2016-77785-

Time-Recovering PCI-AER interface for Bio-inspired Spiking Systems

Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows for real-time virtual massive connectivity between huge number neurons located on different chips. By exploiting high speed digital communication circuits (with nano-seconds timings), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Also, neurons generate ‘events’ according to their activity levels. More active neurons generate more events per unit time, and access the interchip communication channel more frequently, while neurons with low activity consume less communication bandwidth. When building multi-chip muti-layered AER systems it is absolutely necessary to have a computer interface that allows (a) to read AER interchip traffic into the computer and visualize it on screen, and (b) inject a sequence of events at some point of the AER structure. This is necessary for testing and debugging complex AER systems. This paper presents a PCI to AER interface, that dispatches a sequence of events received from the PCI bus with embedded timing information to establish when each event will be delivered. A set of specialized states machines has been introduced to recovery the possible time delays introduced by the asynchronous AER bus. On the input channel, the interface capture events assigning a timestamp and delivers them through the PCI bus to MATLAB applications. It has been implemented in real time hardware using VHDL and it has been tested in a PCI-AER board, developed by authors, that includes a Spartan II 200 FPGA. The demonstration hardware is currently capable to send and receive events at a peak rate of 8,3 Mev/sec, and a typical rate of 1 Mev/sec.European Commission IST-2001-34124Ministerio de Educación y Ciencia TIC-2000-0406-P

Robotics software frameworks for multi-agent robotic systems development

Robotics is an area of research in which the paradigm of Multi-Agent Systems (MAS) can prove to be highly useful. Multi-Agent Systems come in the form of cooperative robots in a team, sensor networks based on mobile robots, and robots in Intelligent Environments, to name but a few. However, the development of Multi-Agent Robotic Systems (MARS) still presents major challenges. Over the past decade, a high number of Robotics Software Frameworks (RSFs) have appeared which propose some solutions to the most recurrent problems in robotics. Some of these frameworks, such as ROS, YARP, OROCOS, ORCA, Open-RTM, and Open-RDK, possess certain characteristics and provide the basic infrastructure necessary for the development of MARS. The contribution of this work is the identification of such characteristics as well as the analysis of these frameworks in comparison with the general-purpose Multi-Agent System Frameworks (MASFs), such as JADE and Mobile-C.Ministerio de Ciencia e Innovación TEC2009-10639-C04-02Junta de Andalucía P06-TIC-2298Junta de Andalucía P08-TIC-0386