Dragan Mišić

A case of using the Semantic Interoperability Framework for custom orthopedic implants manufacturing

Abstract The efficiency and effectiveness of the daily practice in orthopedic surgery depend on the availability, interoperability and unique access to a wide set of information, related to the patient’s medical record and diagnosis, domain knowledge and available resources and staff. The most important of the tangible resources, needed for the therapeutic or preventive actions are orthopedic implants. In some cases, the implants may be highly complex and customized products, which need to be manufactured (assembled) on basis of the above information in a shortest possible timeframe. In this paper, the case of the custom orthopedic implants manufacturing is described from the perspective of the collaborative enterprising, with special consideration of the interoperability issues of the involved enterprise collaboration. It is shown how the previously developed Semantic Interoperability Framework can be used to improve the efficiency of the manufacturing and other relevant processes.

IMPLANT MATERIAL SELECTION USING EXPERT SYSTEM

Most certainly, in the field of medicine there is a great contribution of new techniques and technologies, which is reflected in an entire system of health care services. Customized implants are both fully geometrically and topologically adjusted so as to meet the needs of individual patients, thus making each implant unique. Their production requires joint efforts of a multidisciplinary team of different profile experts who combine their knowledge in the Implant knowledge model. Thus, we develop an expert system which should help or replace humans in the process of Implant material selection. This paper gives an overview of the expert system concept for the given problem. Its task is to carry out a selection of biomaterial (or class of material) for a customized implant. The model significantly improves the efficiency of preoperative planning in orthopaedics.

Analysis of semantic features in free-form objects reconstruction

Abstract One of the biggest challenges associated with design and digital reconstruction of free forms comes from uniqueness and unrepeatability of these shapes. During digital reconstruction of these forms, the designer has to choose the right set of geometric features and then compose them in a way that will enable the most accurate reconstruction of the geometry. While doing this, the designer primarily relies on personal experience gained through work with free-form objects of similar geometry. In our opinion, the analysis of free-form objects geometry should rely upon semantic interpretation of their geometric and other features, and the greatest challenge of automation of digital reconstruction and free-form object design in general is closely related to automation of semantic interpretation of geometric and other free-form object features. In this paper, a case of chest bone implant digital reconstruction is presented, where a new semantic model called the active semantic model was used for modeling the meaning of geometric elements, that is, the semantic features of a free-form object. The active semantic model and its analogy-based reasoning algorithms have shown themselves as applicable for the automation of semantic interpretation of the unique, unrepeatable, and unpredictable forms of chest bone. Moreover, this semantic model showed the potential to help automate selecting and composing of geometric features for efficient digital reconstruction of the geometry of free forms.

Recognizing Topological Analogy in Semantic Network

Recognizing topological analogy between the parts of semantic network seems to be very important step in the process of semantic categorization and interpretation of data that are embedded into the semantic network. Considering the semantic network as a set of graphs, recognition of topological analogy between the parts of semantic network can be treated as maximum common subgraph problem which falls in the group of exact graph matching problems. In this paper authors propose a new algorithm for maximum common subgraph detection aimed to a specific semantic network called Active Semantic Model (ASM). This semantic network can be represented as the set of labeled directed multigraphs with unique node labels. The structure of these graphs is specific because associations or edges are labeled with several attributes and some of them are related to nodes connected by edge. That kind of association-oriented structure enables associations or edges to play key role in the process of semantic categorization and interpretation of data. Furthermore, this kind of structure enables modeling semantic contexts in a form of semantically designated graphs (of associations). Proposed algorithm is capable of recognizing simultaneously maximum common subgraph of input graph and each of the graphs representing different contexts in ASM semantic network.

IT Support for University Spin-Off Companies

Using information technologies can contribute significantly to the successful start of a company and its later progress. However, successful implementation is connected to certain expenses, which smaller companies (such as university spin-off companies) usually cannot afford. The analysis of existing approaches to implementation of IT and information systems will be performed in this chapter, along with the study of applicability of their use in university spin-off companies. As a conclusion, we will propose the best way to choose and use IT systems.

Software Framework for the Creation and Application of Personalized Bone and Plate Implant Geometrical Models

Computer-Assisted Orthopaedic Surgery (CAOS) defines a set of techniques that use computers and other devices for planning, guiding, and performing surgical interventions. The important components of CAOS are accurate geometrical models of human bones and plate implants, which can be used in preoperational planning or for surgical guiding during an intervention. Software framework which is introduced in this study is based on the Model-View-Controller (MVC) architectural pattern, and it uses 3D models of bones and plate implants developed by the application of the Method of Anatomical Features (MAF). The presented framework may be used for preoperative planning processes and for the production of personalized plate implants. The main idea of the research was to develop a novel integrated software framework which will provide improved personalized healthcare to the patient, and at the same time, provide the surgeon with more control over the patients treatment and recovery.

The Modelling Approach of Data and Knowledge Bases of Expert Capp Systems

The paper presents a modelling approach of data and knowledge bases of the CAPP systems based on expert system technology. The model uses a hybrid modelling approach with heuristic and deterministic type of knowledge represented in an integrated knowledge base. If more then one rule can be fired, then its selection will be based upon the Certenity Factors (CF) that specify the priority of rules. The model presented in the paper has some generic features and could be used in other engineering applications with a relatively small modification. The proposed model is implemented in the CAPROT system for process planning of rotational mechanical parts.