Literature DB >> 15072216

Fetal brain MRI: segmentation and biometric analysis of the posterior fossa.

Isabelle Claude1, Jean-Luc Daire, Guy Sebag.   

Abstract

This paper presents a novel approach to fetal magnetic resonance image segmentation and biometric analysis of the posterior fossa's midline structures. We developed a semi-automatic segmentation method (based on a region growing technique) and tested the algorithm on images of 104 normal fetuses. Using the segmented regions of interest (posterior fossa, vermis, and brainstem), we computed four relative area ratios. Statistical and clinical analysis of our results showed that the relative development of these structures appears to be independent of pregnancy term. In an additional study of 23 pathological cases, one of the four measurements was always significantly different from the corresponding value observed in normal cases.

Mesh:

Year:  2004        PMID: 15072216     DOI: 10.1109/TBME.2003.821032

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  8 in total

1.  Prenatal magnetic resonance imaging: brain normal linear biometric values below 24 gestational weeks.

Authors:  C Parazzini; A Righini; M Rustico; D Consonni; F Triulzi
Journal:  Neuroradiology       Date:  2008-06-19       Impact factor: 2.804

Review 2.  Toward the automatic quantification of in utero brain development in 3D structural MRI: A review.

Authors:  Oualid M Benkarim; Gerard Sanroma; Veronika A Zimmer; Emma Muñoz-Moreno; Nadine Hahner; Elisenda Eixarch; Oscar Camara; Miguel Angel González Ballester; Gemma Piella
Journal:  Hum Brain Mapp       Date:  2017-02-14       Impact factor: 5.038

3.  Automatic segmentation of the fetal cerebellum on ultrasound volumes, using a 3D statistical shape model.

Authors:  Benjamín Gutiérrez-Becker; Fernando Arámbula Cosío; Mario E Guzmán Huerta; Jesús Andrés Benavides-Serralde; Lisbeth Camargo-Marín; Verónica Medina Bañuelos
Journal:  Med Biol Eng Comput       Date:  2013-05-18       Impact factor: 2.602

4.  Knowledge-based localization of hippocampus in human brain MRI.

Authors:  Mohammad-Reza Siadat; Hamid Soltanian-Zadeh; Kost V Elisevich
Journal:  Comput Biol Med       Date:  2007-03-06       Impact factor: 4.589

5.  Adaptive prior probability and spatial temporal intensity change estimation for segmentation of the one-year-old human brain.

Authors:  Sun Hyung Kim; Vladimir S Fonov; Cheryl Dietrich; Clement Vachet; Heather C Hazlett; Rachel G Smith; Michael M Graves; Joseph Piven; John H Gilmore; Stephen R Dager; Robert C McKinstry; Sarah Paterson; Alan C Evans; D Louis Collins; Guido Gerig; Martin Andreas Styner
Journal:  J Neurosci Methods       Date:  2012-09-29       Impact factor: 2.390

6.  Atlas-based segmentation of developing tissues in the human brain with quantitative validation in young fetuses.

Authors:  Piotr A Habas; Kio Kim; Francois Rousseau; Orit A Glenn; A James Barkovich; Colin Studholme
Journal:  Hum Brain Mapp       Date:  2010-09       Impact factor: 5.038

7.  Reference biometry of foetal brain by prenatal MRI and the distribution of measurements in foetuses with ventricular septal defect.

Authors:  Feng Xia; Yu Guo; Hua He; Peiwen Chen; Jianbo Shao; Wei Xia
Journal:  Ann Med       Date:  2021-12       Impact factor: 4.709

Review 8.  MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer's Disease: A Survey.

Authors:  Nagaraj Yamanakkanavar; Jae Young Choi; Bumshik Lee
Journal:  Sensors (Basel)       Date:  2020-06-07       Impact factor: 3.576

  8 in total

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