Ratsnake: A Versatile Image Annotation Tool with Application to Computer-Aided Diagnosis

Image segmentation and annotation are key components of image-based medical computer-aided diagnosis (CAD) systems. In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system. In order to demonstrate this unique capability, we present its novel application for the evaluation and quantification of salient objects and structures of interest in kidney biopsy images. Accurate annotation identifying and quantifying such structures in microscopy images can provide an estimation of pathogenesis in obstructive nephropathy, which is a rather common disease with severe implication in children and infants. However a tool for detecting and quantifying the disease is not yet available. A machine learning-based approach, which utilizes prior domain knowledge and textural image features, is considered for the generation of an image force field customizing the presented tool for automatic evaluation of kidney biopsy images. The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains

A novel augmented reality simulator for skills assessment in minimal invasive surgery

Introduction: Over the past decade, simulation-based training has come to the foreground as an efficient method for training and assessment of surgical skills in minimal invasive surgery. Box-trainers and virtual reality (VR) simulators have been introduced in the teaching curricula and have substituted to some extent the traditional model of training based on animals or cadavers. Augmented reality (AR) is a new technology that allows blending of VR elements and real objects within a real-world scene. In this paper, we present a novel AR simulator for assessment of basic laparoscopic skills. Methods: The components of the proposed system include: a box-trainer, a camera and a set of laparoscopic tools equipped with custom-made sensors that allow interaction with VR training elements. Three AR tasks were developed, focusing on basic skills such as perception of depth of field, hand-eye coordination and bimanual operation. The construct validity of the system was evaluated via a comparison between two experience groups: novices with no experience in laparoscopic surgery and experienced surgeons. The observed metrics included task execution time, tool pathlength and two task-specific errors. The study also included a feedback questionnaire requiring participants to evaluate the face-validity of the system. Results: Between-group comparison demonstrated highly significant differences (<0.01) in all performance metrics and tasks denoting the simulator’s construct validity. Qualitative analysis on the instruments’ trajectories highlighted differences between novices and experts regarding smoothness and economy of motion. Subjects’ ratings on the feedback questionnaire highlighted the face-validity of the training system. Conclusions: The results highlight the potential of the proposed simulator to discriminate groups with different expertise providing a proof of concept for the potential use of AR as a core technology for laparoscopic simulation training. © 2014, Springer Science+Business Media New York

PLATO - Intelligent middleware platform for the collection, analysis, processing of data from multiple heterogeneous sensor systems and application development for business intelligence

The "Internet of Things" along with the "Internet ofServices" is expected to undertake a significant role in our lives for the years to come. The versatility of its components and the ability to harvest, as well as consume, ubiquitous services in addition to information from different providers, are among the main challenges for the expansion. Main information producers will consist of networks of small smart objects. These interconnected smart nodes are equipped with different micro controllers, use different network protocols and have different operational requirements. In this paper we propose a framework that confronts all types of heterogeneities in order to manage smart nodes and their data in business intelligence applications. © 2012 IEEE

Mixed (composite) glandular-endocrine cell carcinoma of the gallbladder

Background A mixed pattern of glandular and neuroendocrine elements is rare in tumours at any site within the gastrointestinal tract but particularly so in the gallbladder. Case outline A 72‐year‐old woman presented with abdominal pain and jaundice and was found to have a large mass in the fundus of the gallbladder.The mass was radically excised to include a wedge of liver and the hepatoduodenal lymph nodes. Histopathological examination of the resected gallbladder showed an invasive tumour composed of both adenocarcinoma and endocrine cell carcinoma, with apparent transitions between them. The patient received no further treatment and died two months later. Discussion There are 14 previous case reports of mixed adeno/endocrine carcinoma of the gallbladder. Histochemical similarities between the two neoplastic components of the present tumour would support their origin from a common precursor cell, but the alternative hypothesis of coincidental neoplastic change in two different cell types cannot be excluded