Hit-or-Miss Transform in Multivariate Images

Author(s):  
Santiago Velasco-Forero ◽  
Jesús Angulo
Keyword(s):  
2005 ◽  
Vol 75 (2) ◽  
pp. 115-126 ◽  
Author(s):  
J.C. Noordam ◽  
W.H.A.M. van den Broek ◽  
P. Geladi ◽  
L.M.C. Buydens
Keyword(s):  

1989 ◽  
Vol 5 (3) ◽  
pp. 209-220 ◽  
Author(s):  
Paul Geladi ◽  
Hans Isaksson ◽  
Lennart Lindqvist ◽  
Svante Wold ◽  
Kim Esbensen

2014 ◽  
Vol 34 (1) ◽  
pp. 1 ◽  
Author(s):  
Guillaume Noyel ◽  
Jesus Angulo ◽  
Dominique Jeulin ◽  
Daniel Balvay ◽  
Charles-André Cuenod

We propose a new computer aided detection framework for tumours acquired on DCE-MRI (Dynamic Contrast Enhanced Magnetic Resonance Imaging) series on small animals. To perform this approach, we consider DCE-MRI series as multivariate images. A full multivariate segmentation method based on dimensionality reduction, noise filtering, supervised classification and stochastic watershed is explained and tested on several data sets. The two main key-points introduced in this paper are noise reduction preserving contours and spatio temporal segmentation by stochastic watershed. Noise reduction is performed in a special way to select factorial axes of Factor Correspondence Analysis in order to preserves contours. Then a spatio-temporal approach based on stochastic watershed is used to segment tumours. The results obtained are in accordance with the diagnosis of the medical doctors.


2019 ◽  
Vol 28 (5) ◽  
pp. 2228-2241 ◽  
Author(s):  
Hermine Chatoux ◽  
Noel Richard ◽  
Francois Lecellier ◽  
Christine Fernandez-Maloigne

2013 ◽  
pp. 291-321
Author(s):  
Jesus Angulo ◽  
Jocelyn Chanussot
Keyword(s):  

2004 ◽  
Vol 73 (1) ◽  
pp. 105-117 ◽  
Author(s):  
Neal B. Gallagher ◽  
Jeremy M. Shaver ◽  
Elaine B. Martin ◽  
Julian Morris ◽  
Barry M. Wise ◽  
...  

2005 ◽  
Vol 19 (11-12) ◽  
pp. 607-614 ◽  
Author(s):  
Thanh N. Tran ◽  
Ron Wehrens ◽  
Lutgarde M. C. Buydens

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