Difference between revisions of "Publications/gasnault.21.seminar"
From LRDE
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| year = 2021 |
| year = 2021 |
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| number = 2119 |
| number = 2119 |
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− | | abstract = Brain development can be evaluated using brain Magnetic Resonance Imaging (MRI). It is useful in cases of preterm birth to ensure that no brain disease develops during the postnatal period. Such diseases can be visible on T2-weighted MR image as high signal intensity (DEHSI). To assess the presence of white matter |
+ | | abstract = Brain development can be evaluated using brain Magnetic Resonance Imaging (MRI). It is useful in cases of preterm birth to ensure that no brain disease develops during the postnatal period. Such diseases can be visible on T2-weighted MR image as high signal intensity (DEHSI). To assess the presence of white matter hyperintensitiesthis work implements a new robust, semi-automated frameworkbased on mathematical morphology, specialized on neonate brain segmentation. We will go over the related workthe implementation of the different steps and the difficulties encountered. In the end, the version developped during this internship is not completely finished but it is in good shape for a later finalization. |
| type = techreport |
| type = techreport |
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| id = gasnault.21.seminar |
| id = gasnault.21.seminar |
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− | | lrdepaper = https://www.lrde.epita.fr/dload/202106-Seminar/2119.pdf |
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− | == Source code == |
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− | Source code for this project can be found [https://gitlab.lrde.epita.fr/lgasnault/neobrainseg here]. |
Revision as of 11:22, 31 August 2021
- Authors
- Louis Gasnault
- Type
- techreport
- Year
- 2021
- Number
- 2119
Abstract
Brain development can be evaluated using brain Magnetic Resonance Imaging (MRI). It is useful in cases of preterm birth to ensure that no brain disease develops during the postnatal period. Such diseases can be visible on T2-weighted MR image as high signal intensity (DEHSI). To assess the presence of white matter hyperintensitiesthis work implements a new robust, semi-automated frameworkbased on mathematical morphology, specialized on neonate brain segmentation. We will go over the related workthe implementation of the different steps and the difficulties encountered. In the end, the version developped during this internship is not completely finished but it is in good shape for a later finalization.