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Extraction des tumeurs cérébrales à partir des images scanographiques

Extraction des tumeurs cérébrales à partir des images scanographiques

          
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About the Book

La segmentation des images médicales est une étape cruciale. L'objectif de ce travail était de segmenter des tumeurs cérébrales, à partir des coupes axiales d'examens scanographiques. Notre base de données comporte 20 patients. Le logiciel utilisé est MATLAB. Nous avons proposé quatre méthodes, Level set, une méthode améliorée de Level set et deux méthodes hybrides: Level set-K-means et Level set-Fuzzy C Means. Nous avons débuté, pour diminuer le bruit, par appliquer un filtre de diffusion anisotropique non linéaire. Ensuite, nous avons testé nos quatre méthodes sur notre base de données. Chaque algorithme a ses atouts et ses limites. Enfin et afin d'évaluer la qualité de segmentation, nous avons comparé ces quatre méthodes en utilisant deus métriques: précision et indice d'AUC de la courbe ROC. Nous avons montré que pour la méthode hybride Fuzzy C Means-Level set, la distribution du paramètre précision était la meilleure, la moyenne de ce paramètre était la plus élevée et la valeur de l'AUC était également la plus élevée. Nous avons alors conclu que l'algorithme hybride Level set- Fuzzy C Means était le meilleur.


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Product Details
  • ISBN-13: 9786138425229
  • Publisher: KS Omniscriptum Publishing
  • Publisher Imprint: Editions Universitaires Europeennes
  • Height: 229 mm
  • No of Pages: 80
  • Spine Width: 5 mm
  • Width: 152 mm
  • ISBN-10: 6138425227
  • Publisher Date: 27 Aug 2018
  • Binding: Paperback
  • Language: French
  • Returnable: N
  • Weight: 127 gr


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