An ontology-based module of the information system ScolioMedIS for 3D digital diagnosis of adolescent scoliosis. (September 2019)
- Record Type:
- Journal Article
- Title:
- An ontology-based module of the information system ScolioMedIS for 3D digital diagnosis of adolescent scoliosis. (September 2019)
- Main Title:
- An ontology-based module of the information system ScolioMedIS for 3D digital diagnosis of adolescent scoliosis
- Authors:
- Luković, Vanja
Ćuković, Saša
Milošević, Danijela
Devedžić, Goran - Abstract:
- Highlights: A new ontology-based module of the information system ScolioMedIS is developed. The main functionality of this module is automation of determining Lenke classification of scoliosis. This module uses optical 3D methods and thus avoids the harmful effects of traditional radiation techniques. The module enables frequency analysis of the specific characteristics of the scoliosis according to the Lenke. The module is tested on 35 patients with adolescent idiophatic scoliosis. . Abstract: Background and objective: Conventional information systems are built on top of a relational database. The main weakness of these systems is impossibility to define stable data schema ahead when the knowledge of the system is evolving and dynamic. The widely accepted alternatives to relational databases are ontologies that can be used for designing information systems. Many research papers describe various methods for improving reliability and precision in generating the type of the Lenke classification based on the image processing techniques or a computer program, but all of them require radiograph images. The main objective of this paper is to demonstrate the development of an ontology-based module of the information system ScolioMedIS for adolescent idiopathic scoliosis (AIS) diagnosis and monitoring, which uses optical 3D methods to determine the Lenke classification of AIS and to avoid harmful effects of traditional radiation diagnosis. Methods: For creating an ontology-basedHighlights: A new ontology-based module of the information system ScolioMedIS is developed. The main functionality of this module is automation of determining Lenke classification of scoliosis. This module uses optical 3D methods and thus avoids the harmful effects of traditional radiation techniques. The module enables frequency analysis of the specific characteristics of the scoliosis according to the Lenke. The module is tested on 35 patients with adolescent idiophatic scoliosis. . Abstract: Background and objective: Conventional information systems are built on top of a relational database. The main weakness of these systems is impossibility to define stable data schema ahead when the knowledge of the system is evolving and dynamic. The widely accepted alternatives to relational databases are ontologies that can be used for designing information systems. Many research papers describe various methods for improving reliability and precision in generating the type of the Lenke classification based on the image processing techniques or a computer program, but all of them require radiograph images. The main objective of this paper is to demonstrate the development of an ontology-based module of the information system ScolioMedIS for adolescent idiopathic scoliosis (AIS) diagnosis and monitoring, which uses optical 3D methods to determine the Lenke classification of AIS and to avoid harmful effects of traditional radiation diagnosis. Methods: For creating an ontology-based module of the ScolioMedIS we used the following steps: specification, conceptualization, formalization and implementation. In the specification and conceptualization phase we performed data collection and analysis to define domain, concepts and relationships for ontology design. In the formalization and implementation stage we developed the OBR-Scolio ontology and the ontology-based module of the ScolioMedIS . The module employs the Protégé-OWL API, as a collection of Java interfaces for the OBR-Scolio ontology, which enables the creating, deleting, and editing of the basic elements of the OBR-Scolio ontology, as well as the querying of the ontology. Results: The ontology-based module of ScolioMedIS is tested on the datasets of 20 female and 15 male patients with AIS between the ages of 11 and 18, to categorize spinal curvatures and to automatically generate statistical indicators about the frequency of the basic spinal curvatures, degree of progression or regression of deformity and statistical indicators about curvature characteristics according to the Lenke classification system and Lenke scoliosis types. Results are then compared with analysis of the Lenke classification of 315 observed patients, performed using traditional radiation techniques. Conclusions: This part of the system allows continuous monitoring of the progression/regression of spinal curvatures for each registered patient, which may provide a better management of scoliosis (diagnosis and treatment). … (more)
- Is Part Of:
- Computer methods and programs in biomedicine. Volume 178(2019)
- Journal:
- Computer methods and programs in biomedicine
- Issue:
- Volume 178(2019)
- Issue Display:
- Volume 178, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 178
- Issue:
- 2019
- Issue Sort Value:
- 2019-0178-2019-0000
- Page Start:
- 247
- Page End:
- 263
- Publication Date:
- 2019-09
- Subjects:
- Ontology-based information system -- Adolescent idiopathic scoliosis -- Protégé-OWL API -- Lenke classification
Medicine -- Computer programs -- Periodicals
Biology -- Computer programs -- Periodicals
Computers -- Periodicals
Medicine -- Periodicals
Médecine -- Logiciels -- Périodiques
Biologie -- Logiciels -- Périodiques
Biology -- Computer programs
Medicine -- Computer programs
Periodicals
Electronic journals
610.28 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01692607 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cmpb.2019.06.027 ↗
- Languages:
- English
- ISSNs:
- 0169-2607
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.095000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 11355.xml