1 / 1

Ayman El-Baz 1 , Seniha E. Yuksel 1 , Hongjian Shi 1 , Aly A. Farag 1 ,

2D and 3D Shape Based Segmentation Using Deformable Models. #S32. Ayman El-Baz 1 , Seniha E. Yuksel 1 , Hongjian Shi 1 , Aly A. Farag 1 , Mohamed A. El-Ghar 2 , Tarek Eldiasty 2 , Mohamed A. Ghoneim 2 1 Computer Vision and Image Processing Lab, University of Louisville

yuki
Download Presentation

Ayman El-Baz 1 , Seniha E. Yuksel 1 , Hongjian Shi 1 , Aly A. Farag 1 ,

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 2D and 3D Shape Based Segmentation Using Deformable Models #S32 Ayman El-Baz1, Seniha E. Yuksel1, Hongjian Shi1, Aly A. Farag1, Mohamed A. El-Ghar2, Tarek Eldiasty2, Mohamed A. Ghoneim2 1Computer Vision and Image Processing Lab, University of Louisville 2Mansoura University, Urology and Nephrology Center Prior Shape Deformable Model Assuming object: Assuming background: Signed distance map and gray level densities are estimated with our modified EM algorithm Evolve if: Current Gray Level Results & Validation Result at -1.9dB SNR Average shape by FEM

More Related