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Official Journal of the , the International Union of Phlebology and the
Indexed/Abstracted in: BIOSIS Previews, Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index Expanded (SciSearch), Scopus
Impact Factor 0,899
Molinari F. 1, Meiburger K. M. 1, Zeng G. 2, Saba L. 3, Rajendra Acharya U. 4, Famiglietti L. 3, Georgiou N. 5, Nicolaides A. 5, Sriswan Mamidi R. 6, Kuper H. 7, Suri J. S. 8, 9
1 Biolab, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy;
2 Mayo Clinic, Rochester, MN, USA;
3 Department of Radiology, Azienda Ospedaliera Universitaria di Cagliari, Cagliari, Italy;
4 Department ECE, Ngee Ann Polytechnic, Singapore;
5 Vascular Screening and Diagnostic Centre, London, and Department of Biological Sciences, University of Cyprus, Nicosia, Cyprus;
6 National Institute of Nutrition, Hyderabad, India;
7 Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK;
8 Research Professor (Affiliated), Biomedical Engineering, Idaho State University, Pocatello, ID, USA;
9 Global Biomedical Technologies inc., Roseville, CA, USA
AIM:The aim of this paper was to demonstrate the usage of an automated computer-based IMT measurement system called - CALEX 3.0 (a class of patented AtheroEdge™ software) on a low contrast and low resolution image database acquired during an epidemiological study from India. The image contrast was very low with pixel density of 12.7 pixels/mm. Further, to demonstrate the accuracy and reproducibility of the AtheroEdge™ software system we compared it with the manual tracings of a vascular surgeon – considered as a gold standard.
METHODS: We automatically measured the IMT value of 885 common carotid arteries in longitudinal B-Mode images. CALEX 3.0 consisted of a stage for the automatic recognition of the carotid artery and an IMT measurement modulus made of a fuzzy K-means classifier. Performance was assessed by measuring the system accuracy and reproducibility against manual tracings by experts.
RESULTS: CALEX 3.0 processed all the 885 images of the dataset (100% success). The average automated obtained IMT measurement by CALEX 3.0 was 0.407±0.083 mm compared with 0.429 ± 0.052 mm for the manual tracings, which led to an IMT bias of 0.022±0.081mm. The IMT measurement accuracy (0.022 mm) was comparable to that obtained on high-resolution images and the reproducibility (0.081 mm) was very low and suitable to clinical application. The Figure-of-Merit defined as the percent agreement between the computer-estimated IMT and manually measured IMT for CALEX 3.0 was 94.7%.
CONCLUSION:CALEX 3.0 had a 100% success in processing low contrast/low-resolution images. CALEX 3.0 is the first technique, which has led to high accuracy and reproducibility on low-resolution images acquired during an epidemiological study. We propose CALEX 3.0 as a generalized framework for IMT measurement on large datasets.