Difference between revisions of "NeoBrainSeg"

Revision as of 11:24, 3 May 2018

The Challenge of Cerebral MRI in Neonates: A New Method using Mathematical Morphology for the Segmentation of Structures Including DEHSI

Publication

The related publication is available from this page.

Bibtex entry:

@Article{         xu.18.media,
  author        = {Yongchao Xu and Baptiste Morel and Sonia Dahdouh and
                   \'Elodie Puybareau and Alessio Virz\`i and H\'el\`ene
		   Urien and Thierry~G\'eraud and Catherine Adamsbaum and
		   Isabelle Bloch},
  title         = {The Challenge of Cerebral Magnetic Resonance Imaging in
                   Neonates: {A} New Method using Mathematical Morphology
		   for the Segmentation of Structures Including Diffuse
		   Excessive High Signal Intensities},
  journal       = {Medical Image Analysis},
  year          = 2018,
  pages         = {1--23},
  url =	 {http://publications.lrde.epita.fr/xu.18.media},
  note = {To appear}
}

Software

Available soon...

If this software is used in the context of a scientific publication, please cite the paper mentioned above.

Copyright Notice

The copyright holders of the main code included in the archive are:

LRDE
FIXME
FIXME

You are allowed to use these codes and software for research purpose. If so, please specify the following copyright: "Copyright (c) 2018. EPITA Research and Development Laboratory (LRDE)". You are not allowed to redistribute these codes. You are not allowed to redistribute the dehsi.nii example.

@@ Line 6: / Line 6: @@
 Bibtex entry:
-<nowiki>
+<pre>
 @Article{         xu.18.media,
   author        = {Yongchao Xu and Baptiste Morel and Sonia Dahdouh and
@@ Line 20: / Line 20: @@
   year          = 2018,
   pages         = {1--23},
+  url =	 {http://publications.lrde.epita.fr/xu.18.media},
-  abstract      = {Preterm birth is a multifactorial condition associated
-                  with increased morbidity and mortality. Diffuse excessive
-                  high signal intensity (DEHSI) has been recently described
-                  on T2-weighted MR sequences in this population and thought
-                  to be associated with neuropathologies. To date, no robust
-                  and reproducible method to assess the presence of white
-                  matter hyperintensities has been developed, perhaps
-                  explaining the current controversy over their prognostic
-                  value. The aim of this paper is to propose a new
-                  semi-automated framework to detect DEHSI on neonatal brain
-                  MR images having a particular pattern due to the
-                  physiological lack of complete myelination of the white
-                  matter.  A novel method for semi- automatic segmentation
-                  of neonatal brain structures and DEHSI, based on
-                  mathematical morphology and on max-tree representations of
-                  the images is thus described.  It is a mandatory first
-                  step to identify and clinically assess homogeneous cohorts
-                  of neonates for DEHSI and/or volume of any other segmented
-                  structures.  Implemented in a user-friendly interface, the
-                  method makes it straightforward to select relevant markers
-                  of structures to be segmented, and if needed, apply
-                  eventually manual corrections. This method responds to the
-                  increasing need for providing medical experts with
-                  semi-automatic tools for image analysis, and overcomes the
-                  limitations of visual analysis alone, prone to
-                  subjectivity and variability. Experimental results
-                  demonstrate that the method is accurate, with excellent
-                  reproducibility and with very few manual corrections
-                  needed. Although the method was intended initially for
-                  images acquired at 1.5T, which corresponds to usual
-                  clinical practice, preliminary results on images acquired
-                  at 3T suggest that the proposed approach can be
-                  generalized.},
-  url =	 {http://publications.lrde.epita.fr/xu.18.media.pdf},
   note = {To appear}
 }
-</nowiki>
+</pre>
@@ Line 67: / Line 34: @@
 ==== Copyright Notice ====
-[http://www.lrde.epita.fr LRDE] is the copyright holder of all the codes included in the archive.
+The copyright holders of the main code included in the archive are:
+* [http://www.lrde.epita.fr LRDE]
+* FIXME
+* FIXME
 You are allowed to use these codes and software for research purpose. If so, please specify the following copyright: "Copyright (c) 2018. EPITA Research and Development Laboratory (LRDE)". You are '''not''' allowed to redistribute these codes.