Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Graph analysis of functional brain networks: practical issues in translational neuroscience

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires a know-how of all the methodological steps of the processing pipeline that manipulates the input brain signals and extract the functional network properties. On the other hand, a knowledge of the neural phenomenon under study is required to perform physiological-relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Report on the evaluation of surveillance systems relevant to zoonotic diseases in Kenya, 2015: A basis for design of an integrated human–livestock surveillance system

The Zoonoses in Livestock in Kenya (ZooLinK) is a project that seeks to enable Kenya develop an effective surveillance programme for zoonotic diseases (infectious diseases transmissible between animals and human beings). The surveillance programme will be integrated across both human and animal health sectors. To achieve this goal the project will work in close collaboration with Kenyan government departments in responsible for animal and human health. As a prelude to the start of the project, an evaluation of the existing surveillance systems for human and animal health was carried out. The evaluation focused on the national surveillance system and the systems at the western part of Kenya (Busia county, Kakamega county and Bungoma county) where the initial programme will be developed. In conducting the evaluation the investigators used key informant interviews, focused group discussion participant questionnaires, audio recordings and observation for data collection. Data analysis for the qualitative data focused on generating themes or theory around the responses obtained in the key informants interviews and focused group discussions. Univariate analysis was performed by use of simple proportions in calculation for surveillance system attributes like sensitivity, completeness, PVP and Timeliness for the human health surveillance systems. The findings of the evaluation revealed that there was poor linkage between animal health surveillance and the human health surveillance systems. None of the systems had surveillance structures dedicated to zoonotic diseases. Most practitioners used clinical signs for diagnosis of diseases with little reference to acceptable case definitions. Laboratory diagnosis in animal health services focused more on suspected notifiable diseases as opposed to being a standard operating procedure for diagnosis. In Human health services the health care facilities that had laboratory within the facility conducted laboratory diagnosis for cases referred by the clinicians. However, some clinicians preferred using clinical signs for diagnosis to avoid the wait or turn-around time in the laboratory. For effective surveillance of zoonoses to be realized it would be advisable to establish surveillance structures specific to zoonoses and the necessary resources allocated to the surveillance activities. In addition, an integrated approach that incorporated both human and animal disease surveillance should be employed in the surveillance of zoonoses

Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)