Skin lesions image analysis utilizing smartphones and cloud platforms.

This chapter presents the state of the art on mobile teledermoscopy applications, utilizing smartphones able to store digital images of skin areas depicting regions of interest (lesions) and perform self-assessment or communicate the captured images with expert physicians. Mobile teledermoscopy systems consist of a mobile application that can acquire and identify moles in skin images and classify them according their severity and Cloud infrastructure exploiting computational and storage resources. The chapter presents some indicative mobile applications for skin lesions assessment and describes a proposed system developed by our team that can perform skin lesion evaluation both on the phone and on the Cloud, depending on the network availability.

Automated skin lesion assessment using mobile technologies and cloud platforms.

This paper presents a smart phone based system for storing digital images of skin areas depicting regions of interest (lesions) and performing self-assessment of these skin lesions within these areas. The system consists of a mobile application that can acquire and identify moles in skin images and classify them according their severity into melanoma, nevus and benign lesions. The proposed system includes also a cloud infrastructure exploiting computational and storage resources. This cloud-based architecture provides interoperability and support of various mobile environments as well as flexibility in enhancing the classification model. Initial evaluation results are quite promising and indicate that the application can be used for the task of skin lesions initial assessment.

Advanced characterization of microscopic kidney biopsies utilizing image analysis techniques.

Correct annotation and identification of salient regions in Kidney biopsy images can provide an estimation of pathogenesis in obstructive nephropathy. This paper presents a tool for the automatic or manual segmentation of such regions along with methodology for their characterization in terms of the exhibited pathology. The proposed implementation is based on custom code written in Java and the utilization of open source tools (i.e. RapidMiner, ImageJ). The corresponding implementation details along with the initial evaluation of the proposed integrated system are also presented in the paper.

Emergency fall incidents detection in assisted living environments utilizing motion, sound, and visual perceptual components.

This paper presents the implementation details of a patient status awareness enabling human activity interpretation and emergency detection in cases, where the personal health is threatened like elder falls or patient collapses. The proposed system utilizes video, audio, and motion data captured from the patient's body using appropriate body sensors and the surrounding environment, using overhead cameras and microphone arrays. Appropriate tracking techniques are applied to the visual perceptual component enabling the trajectory tracking of persons, while proper audio data processing and sound directionality analysis in conjunction to motion information and subject's visual location can verify fall and indicate an emergency event. The postfall visual and motion behavior of the subject, which indicates the severity of the fall (e.g., if the person remains unconscious or patient recovers) is performed through a semantic representation of the patient's status, context and rules-based evaluation, and advanced classification. A number of advanced classification techniques have been examined in the framework of this study and their corresponding performance in terms of accuracy and efficiency in detecting an emergency situation has been thoroughly assessed.

GRISSOM platform: enabling distributed processing and management of biological data through fusion of grid and web technologies.

Transcriptomic technologies have a critical impact in the revolutionary changes that reshape biological research. Through the recruitment of novel high-throughput instrumentation and advanced computational methodologies, an unprecedented wealth of quantitative data is produced. Microarray experiments are considered high-throughput, both in terms of data volumes (data intensive) and processing complexity (computationally intensive). In this paper, we present grids for in silico systems biology and medicine (GRISSOM), a web-based application that exploits GRID infrastructures for distributed data processing and management, of DNA microarrays (cDNA, Affymetrix, Illumina) through a generic, consistent, computational analysis framework. GRISSOM performs versatile annotation and integrative analysis tasks, through the use of third-party application programming interfaces, delivered as web services. In parallel, by conforming to service-oriented architectures, it can be encapsulated in other biomedical processing workflows, with the help of workflow enacting software, like Taverna Workbench, thus rendering access to its algorithms, transparent and generic. GRISSOM aims to set a generic paradigm of efficient metamining that promotes translational research in biomedicine, through the fusion of grid and semantic web computing technologies.

Mobile healthcare information management utilizing Cloud Computing and Android OS.

Cloud Computing provides functionality for managing information data in a distributed, ubiquitous and pervasive manner supporting several platforms, systems and applications. This work presents the implementation of a mobile system that enables electronic healthcare data storage, update and retrieval using Cloud Computing. The mobile application is developed using Google's Android operating system and provides management of patient health records and medical images (supporting DICOM format and JPEG2000 coding). The developed system has been evaluated using the Amazon's S3 cloud service. This article summarizes the implementation details and presents initial results of the system in practice.

An open data mining framework for the analysis of medical images: application on obstructive nephropathy microscopy images.

This paper presents an open image-mining framework that provides access to tools and methods for the characterization of medical images. Several image processing and feature extraction operators have been implemented and exposed through Web Services. Rapid-Miner, an open source data mining system has been utilized for applying classification operators and creating the essential processing workflows. The proposed framework has been applied for the detection of salient objects in Obstructive Nephropathy microscopy images. Initial classification results are quite promising demonstrating the feasibility of automated characterization of kidney biopsy images.

Enabling distributed processing and management of biological data using the grid and web technologies.

Transcriptomic technologies have dramatically reshaped modern biological research by deriving profiles of genome-wide expression of living organisms, and producing an unprecedented wealth of quantitative data. Given this characteristic, microarray experiments are considered high-throughput both in terms of data (data intensive) and processing (computationally intensive). GRISSOM Web Tools enable the exploitation of GRID resources for DNA microarray data distributed processing and management. It provides experts with a complete web-based solution for managing, searching and disseminating biological knowledge in the context of gene expression patterns on a genomic scale. Through the incorporation of novel workflows and various web services, the platform is gradually transformed to a powerful environment for knowledge discovery in the biomedical research.

Wavelet-based compression with ROI coding support for mobile access to DICOM images over heterogeneous radio networks.

Most of the commercial medical image viewers do not provide scalability in image compression and/or region of interest (ROI) encoding/decoding. Furthermore, these viewers do not take into consideration the special requirements and needs of a heterogeneous radio setting that is constituted by different access technologies [e.g., general packet radio services (GPRS)/ universal mobile telecommunications system (UMTS), wireless local area network (WLAN), and digital video broadcasting (DVB-H)]. This paper discusses a medical application that contains a viewer for digital imaging and communications in medicine (DICOM) images as a core module. The proposed application enables scalable wavelet-based compression, retrieval, and decompression of DICOM medical images and also supports ROI coding/decoding. Furthermore, the presented application is appropriate for use by mobile devices activating in heterogeneous radio settings. In this context, performance issues regarding the usage of the proposed application in the case of a prototype heterogeneous system setup are also discussed.

Overview of advanced computer vision systems for skin lesions characterization.

During the last years, computer-vision-based diagnosis systems have been used in several hospitals and dermatology clinics, aiming mostly at the early detection of skin cancer, and more specifically, the recognition of malignant melanoma tumour. In this paper, we review the state of the art in such systems by first presenting the installation, the visual features used for skin lesion classification, and the methods for defining them. Then, we describe how to extract these features through digital image processing methods, i.e., segmentation, border detection, and color and texture processing, and we present the most prominent techniques for skin lesion classification. The paper reports the statistics and the results of the most important implementations that exist in the literature, while it compares the performance of several classifiers on the specific skin lesion diagnostic problem and discusses the corresponding findings.

Computer-supported angiogenesis quantification using image analysis and statistical averaging.

Angiogenesis is a complex process, involving multiple crosstalks among tumor, endothelial, and stromal cells in order to establish a biochemical network for oxygen and nutrients supply, necessary for the promotion of tumor growth. In this sense, measuring angiogenic activity is considered an informative marker of tumor growth or its inhibition. One of the most popular testbeds for the study of angiogenesis is developing chick embryo and its chorioallantoic membrane (CAM). In this paper, an automated image analysis and statistical processing method for the extraction of features informative for the angiogenic process is proposed and a Web-based tool that provides an unbiased quantification of the microvessel density and growth in angiogenic CAM images is described. The applicability of the tool is tested in two datasets, concerning: 1) the quantification and subsequent detection of tumor growth at different stages of embryonic development and 2) the inhibitory effect of dexamethasone (i.e., an inhibitor of the angiogenesis phenomenon) over a series of CAM samples. Experimental results presented in this paper indicate the efficiency of the automated angiogenesis quantification method regarding both tumor growth and inhibition detection.

Automated cell apoptosis characterization using active contours.

Programmed cell death, also known as apoptosis, is of fundamental importance in many biological processes and also highly associated with serious diseases like cancer and HIV. The current paper presents an innovative method for apoptosis phenomenon characterization based on apoptotic cell quantification and detection using active contours (snakes). Evaluation results against manual counts have proved the high accuracy and efficiency of the developed method.

Advanced medical video services through context-aware medical networks.

The aim of this paper is to present a framework for advanced medical video delivery services, through network and patient-state awareness. Under this scope a context-aware medical networking platform is described. The developed platform enables proper medical video data coding and transmission according to both a) network availability and/or quality and b) patient status, optimizing thus network performance and telediagnosis. An evaluation platform has been developed based on scalable H.264 coding of medical videos. Corresponding results of video transmission over a WiMax network have proved the effectiveness and efficiency of the platform providing proper video content delivery.