Medical Image Analysis represents a very important step in clinical diagnosis. It provides image segmentation of the Region of Interest (ROI) and the generation of a three-dimensional model, representing the selected object. In this work, was proposed a neural network segmentation based on Self-Organizing Maps (SOM) and a three-dimensional SOM architecture to create a 3D model, starting from 2D data of extracted contours. The utilized dataset consists of a set of CT images of patients presenting a prosthesis’ implant, in DICOM format. An application was developed in Visual C++, which provides an user interface to visualize DICOM images and relative segmentation. Moreover it generates a three-dimensional model of the segmented region using Direct3D

A neural network approach to medical image segmentation and Three-Dimensional Reconstruction / Bevilacqua, Vitoantonio; Mastronardi, Giuseppe; Marinelli, Mario (LECTURE NOTES IN COMPUTER SCIENCE). - In: Intelligent Computing: International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006: proceedings, part 1 / [a cura di] De-Shuang Huang, Kang Li, George William Irwin. - Berlin, Heidelberg : Springer, 2006. - ISBN 978-3-540-37271-4. - pp. 22-31 [10.1007/11816157_3]

A neural network approach to medical image segmentation and Three-Dimensional Reconstruction

BEVILACQUA, Vitoantonio;MASTRONARDI, Giuseppe;Mario Marinelli
2006-01-01

Abstract

Medical Image Analysis represents a very important step in clinical diagnosis. It provides image segmentation of the Region of Interest (ROI) and the generation of a three-dimensional model, representing the selected object. In this work, was proposed a neural network segmentation based on Self-Organizing Maps (SOM) and a three-dimensional SOM architecture to create a 3D model, starting from 2D data of extracted contours. The utilized dataset consists of a set of CT images of patients presenting a prosthesis’ implant, in DICOM format. An application was developed in Visual C++, which provides an user interface to visualize DICOM images and relative segmentation. Moreover it generates a three-dimensional model of the segmented region using Direct3D
2006
Intelligent Computing: International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006: proceedings, part 1
978-3-540-37271-4
Springer
A neural network approach to medical image segmentation and Three-Dimensional Reconstruction / Bevilacqua, Vitoantonio; Mastronardi, Giuseppe; Marinelli, Mario (LECTURE NOTES IN COMPUTER SCIENCE). - In: Intelligent Computing: International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006: proceedings, part 1 / [a cura di] De-Shuang Huang, Kang Li, George William Irwin. - Berlin, Heidelberg : Springer, 2006. - ISBN 978-3-540-37271-4. - pp. 22-31 [10.1007/11816157_3]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/13099
Citazioni
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 3
social impact