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Image Edge Detection Using Fractional Conformable Derivatives in Liouville-Caputo Sense for Medical Image Processing
Published in Devendra Kumar, Jagdev Singh, Fractional Calculus in Medical and Health Science, 2020
J. E. Lavín-Delgado, J. E. Solís-Pérez, J. F. Gómez-Aguilar, R. F. Escobar-Jiménez
Arteriovenous malformations (AVMs) are defects in the vascular system, consisting of tangles of abnormal blood vessels (nidus) in which the feeding arteries are directly connected to a venous drainage network without the interposition of a capillary bed [48]. An AVM can happen anywhere in the body, but brain AVMs present substantial risks when they bleed because they can rupture and bleed into the brain. Most AVMs can be detected with either a computed tomography (CT) brain scan or a magnetic resonance imaging (MRI) brain scan [49]. In this sense, it is interesting to implement the operator proposed in these types of medical images with the objective to identify potential AVMs. Figures 1.6 and 1.8 show MRIs of brains taken from [50] and [51], respectively; whereas those in Figures 1.7 and 1.9 show CTs taken from [52] and [53], respectively. All the preceding images are depicted without contrast enhancement. The experimental results show that the proposed operator improves the texture and contrast, thus achieving a more precise detection of AVMs.
Review on the current treatment status of vein of Galen malformations and future directions in research and treatment
Published in Expert Review of Medical Devices, 2021
Panagiotis Primikiris, Georgios Hadjigeorgiou, Maria Tsamopoulou, Alessandra Biondi, Christina Iosif
Gene mutations have been identified in two Mendelian autosomal dominant syndromes with incomplete penetrance and expressivity [111,112], both of which are infrequently associated with VOGMs: capillary malformation-arteriovenous malformation syndrome (RASA1) and hereditary hemorrhagic telangiectasia (ENG and ACVRL1) [110].