Add to ORKGWe present a segmentation method for fetal brain tissuesof T2w MR images, based on the well known ExpectationMaximization Markov Random Field (EM- MRF) scheme. Ourmain contribution is an intensity model composed of 7Gaussian distribution designed to deal with the largeintensity variability of fetal brain tissues. The secondmain contribution is a 3-steps MRF model that introducesboth local spatial and anatomical priors given by acortical distance map. Preliminary results on 4 subjectsare presented and evaluated in comparison to manualsegmentations showing that our methodology cansuccessfully be applied to such data, dealing with largeintensity variability within brain tissues and partialvolume (PV)
This paper describes results for an ongoing research on the segmentation of the posterior fossa and ...
Magnetic resonance imaging (MRI) is becoming increasingly popular as a second-level technique, perfo...
We present a fully automated algorithm for tissue segmentation of noisy, low contrast magnetic reson...
Abstract. We present a segmentation method for fetal brain tissues of T2w MR images, based on the we...
In this work we present a method for the image anal-ysis of Magnetic Resonance Imaging (MRI) of fetu...
The human brain undergoes drastic development in its anatomy and organization from the last trimeste...
MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development...
MR images of the fetus allow non-invasive analysis of the fetal brain. Quantitative analysis of feta...
The objective of this study is the development of an automatic segmentation framework to measure the...
To completely comprehend neurodevelopment in healthy and congenitally abnormal fetuses, quantitative...
It is critical to quantitatively analyse the developing human fetal brain in order to fully understa...
It is critical to quantitatively analyse the developing human fetal brain in order to fully understa...
This electronic version was submitted by the student author. The certified thesis is available in th...
A statistical model is presented that represents the distributions of major tissue classes in single...
International audienceAccurate tissue and structure segmentation of magnetic resonance (MR) brain sc...
This paper describes results for an ongoing research on the segmentation of the posterior fossa and ...
Magnetic resonance imaging (MRI) is becoming increasingly popular as a second-level technique, perfo...
We present a fully automated algorithm for tissue segmentation of noisy, low contrast magnetic reson...
Abstract. We present a segmentation method for fetal brain tissues of T2w MR images, based on the we...
In this work we present a method for the image anal-ysis of Magnetic Resonance Imaging (MRI) of fetu...
The human brain undergoes drastic development in its anatomy and organization from the last trimeste...
MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development...
MR images of the fetus allow non-invasive analysis of the fetal brain. Quantitative analysis of feta...
The objective of this study is the development of an automatic segmentation framework to measure the...
To completely comprehend neurodevelopment in healthy and congenitally abnormal fetuses, quantitative...
It is critical to quantitatively analyse the developing human fetal brain in order to fully understa...
It is critical to quantitatively analyse the developing human fetal brain in order to fully understa...
This electronic version was submitted by the student author. The certified thesis is available in th...
A statistical model is presented that represents the distributions of major tissue classes in single...
International audienceAccurate tissue and structure segmentation of magnetic resonance (MR) brain sc...
This paper describes results for an ongoing research on the segmentation of the posterior fossa and ...
Magnetic resonance imaging (MRI) is becoming increasingly popular as a second-level technique, perfo...
We present a fully automated algorithm for tissue segmentation of noisy, low contrast magnetic reson...