Ms. Amele Florence Kouvahe Profile

Amele Florence Kouvahe

Student at Télécom SudParis

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Publications (2)

Proceedings Article | 13 March 2019 Presentation + Paper

Efficient detection of vascular structures using locally connected filtering

Amele Florence Kouvahe, Catalin Fetita

Proceedings Volume 10950, 109501P (2019) https://doi.org/10.1117/12.2511962

KEYWORDS: Image segmentation, Image filtering, Liver, Lung, Digital filtering, Databases, 3D image processing, Computed tomography, Binary data, Linear filtering

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Proceedings Article | 3 March 2017 Presentation + Paper

Automatic detection and quantification of pulmonary arterio-venous malformations in hereditary hemorrhagic telangiectasia

Catalin Fetita, Thierry Fortemps de Loneux, Amélé Florence Kouvahe, Mostafa El Hajjam

Proceedings Volume 10134, 1013419 (2017) https://doi.org/10.1117/12.2254754

KEYWORDS: Mathematical modeling, Skin, Capillaries, Image segmentation, Glasses, Scanners, Databases

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Hereditary hemorrhagic telangiectasia (HHT) is an autosomic dominant disorder, which is characterized by the development of multiple arterio-venous malformations in the skin, mucous membranes, and/or visceral organs. Pulmonary Arterio-Venous Malformation (PAVM) is an abnormal connection where feeding arteries shunt directly into draining veins with no intervening capillary bed. This condition may lead to paradoxical embolism and hemorrhagic complications. PAVMs patients should systematically be screened as the spontaneous complication rate is high, reaching almost 50%. Chest enhanced contrast CT scanner is the reference screening and follow-up examination. When performed by experienced operators as the prime treatment, percutaneous embolization of PAVMs is a safe, efficient and sustained therapy. The accuracy of PAVM detection and quantification of its progression over time is the key of embolotherapy success. In this paper, we propose an automatic method for PAVM detection and quantification relying on a modeling of vessel deformation, i.e. local caliber increase, based on mathematical morphology. The pulmonary field and vessels are first segmented using geodesic operators. The vessel caliber is estimated by means of a granulometric measure and the local caliber increase is detected by using a geodesic operator, the h-maxdomes. The detection sensitivity can be tuned up according to the choice of the h value which models the irregularity of the vessel caliber along its axis and the PAVM selection is performed according to a clinical criterion of >3 mm diameter of the feeding artery of the PAVM. The developed method was tested on a 20 patient dataset. A sensitivity study allowed choosing the irregularity parameter to maximize the true positive ratio reaching 85.4% in average. A specific false positive reduction procedure targeting the vessel trunks of the arterio-venous tree near mediastinum allows a precision increase from 13% to 67% with an average number of 1.15 false positives per scan.

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