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Use of Fuzzy Neural Network in Diagnosing Postmenopausal Women with Osteoporosis Based on Dental Panoramic Radiographs
Author(s) -
Agus Zainal Arifin,
Akira Asano,
Akira Taguchi,
Takashi Nakamoto,
Masahiko Ohtsuka,
Mikio Tsuda,
Yoshiki Kudo,
Keiji Tanimoto
Publication year - 2007
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2007.p1049
Subject(s) - medicine , osteoporosis , computer science , radiography , artificial neural network , artificial intelligence , thresholding , dentistry , orthodontics , radiology , image (mathematics) , pathology
A thin or eroded cortex of the mandible detected on dental panoramic radiographs is independently associated with low skeletal bone mineral density (BMD) or osteoporosis in postmenopausal women. The purposes of this study were to develop new computer-aided diagnosis system that combines these two panoramic measures by using fuzzy neural networks (FNN) for identifying postmenopausal women with osteoporosis. Dental panoramic radiographs of 100 postmenopausal women who visited our clinic and had BMD assessments at the lumbar spine and the femoral neck were used in this study. Mandibular cortical width and shape were measured by computer-aided systems and used as the inputs. This system partitioned the input space into a set of subspaces using a novel fuzzy thresholding and constructed the fuzzy inference system incorporated with multi layer perceptron neural network. Our results show that the combination of cortical width and shape by using FNN can be used for the identification of postmenopausal women with osteoporosis in dental clinic. Dentists may identify postmenopausal women accurately by using the new FNN based system and refer them to medical professional for BMD testing.

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