Bone microarchitecture characterization ...
Document type :
Article dans une revue scientifique: Article original
DOI :
Title :
Bone microarchitecture characterization based on fractal analysis in spatial frequency domain imaging
Author(s) :
Zehani, Soraya [Auteur]
Laboratoire Energie Signal Images et Automatique [Univ Ngaoundéré] [LESIA]
Ouahabi, Abdeldjalil [Auteur correspondant]
Imaging, Brain & Neuropsychiatry [iBraiN]
Oussalah, Mourad [Auteur]
Mimi, Malika [Auteur]
Tahleb Ahmed, Abdelmalik [Auteur]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Laboratoire Energie Signal Images et Automatique [Univ Ngaoundéré] [LESIA]
Ouahabi, Abdeldjalil [Auteur correspondant]
Imaging, Brain & Neuropsychiatry [iBraiN]
Oussalah, Mourad [Auteur]
Mimi, Malika [Auteur]
Tahleb Ahmed, Abdelmalik [Auteur]
COMmunications NUMériques - IEMN [COMNUM - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Journal title :
International Journal of Imaging Systems and Technology
Pages :
141-159
Publisher :
Wiley
Publication date :
2021-03
ISSN :
0899-9457
English keyword(s) :
discrete cosine transform (DCT)
fractal analysis
medical imaging
osteoporosis
trabecular bone texture
fractal analysis
medical imaging
osteoporosis
trabecular bone texture
HAL domain(s) :
Sciences de l'ingénieur [physics]
Informatique [cs]
Informatique [cs]/Réseaux et télécommunications [cs.NI]
Informatique [cs]/Intelligence artificielle [cs.AI]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Sciences de l'ingénieur [physics]/Electronique
Informatique [cs]
Informatique [cs]/Réseaux et télécommunications [cs.NI]
Informatique [cs]/Intelligence artificielle [cs.AI]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Sciences de l'ingénieur [physics]/Electronique
English abstract : [en]
This paper suggests a new technique for trabecular bone characterization using fractal analysis of X-Ray and MRI texture images for osteoporosis diagnosis. Osteoporosis is a chronic disease characterized by a decrease in ...
Show more >This paper suggests a new technique for trabecular bone characterization using fractal analysis of X-Ray and MRI texture images for osteoporosis diagnosis. Osteoporosis is a chronic disease characterized by a decrease in bone density that can lead to fracture and disability. In essence, the proposed fractal model makes use of the differential box-counting method (DBCM) to estimate the fractal dimension (FD) after an appropriate image preprocessing stage that ensures a robust estimation process. In this study, we showed that within the frequency domain generated through discrete cosine transform (DCT), only a quarter of DCT coefficients are enough to characterize osteoporotic tissues. The algorithmic complexity of the developed approach is of the order of N8log2N8 where N stands for the size of the image, which, in turn, likely yields important gain in terms of medication cost. We report a successful separation of healthy and pathological cases in term of both P - value (using statistical Wilcoxon rank sum test) and margin difference. A comparative statistical analysis has been performed using a publicly available database that contains a set of MRI and X-Ray texture images of both healthy and osteoporotic bone tissues. The statistical results demonstrated the feasibility and accepted performance level of our fractal model-based diagnosis to discriminate healthy and unhealthy trabecular bone tissues. The developed approach has been implemented on a medical device prototype.Show less >
Show more >This paper suggests a new technique for trabecular bone characterization using fractal analysis of X-Ray and MRI texture images for osteoporosis diagnosis. Osteoporosis is a chronic disease characterized by a decrease in bone density that can lead to fracture and disability. In essence, the proposed fractal model makes use of the differential box-counting method (DBCM) to estimate the fractal dimension (FD) after an appropriate image preprocessing stage that ensures a robust estimation process. In this study, we showed that within the frequency domain generated through discrete cosine transform (DCT), only a quarter of DCT coefficients are enough to characterize osteoporotic tissues. The algorithmic complexity of the developed approach is of the order of N8log2N8 where N stands for the size of the image, which, in turn, likely yields important gain in terms of medication cost. We report a successful separation of healthy and pathological cases in term of both P - value (using statistical Wilcoxon rank sum test) and margin difference. A comparative statistical analysis has been performed using a publicly available database that contains a set of MRI and X-Ray texture images of both healthy and osteoporotic bone tissues. The statistical results demonstrated the feasibility and accepted performance level of our fractal model-based diagnosis to discriminate healthy and unhealthy trabecular bone tissues. The developed approach has been implemented on a medical device prototype.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Source :
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