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Measurement of the Stratum Radiatum/Lacunosum-Moleculare (SRLM) [chapter]

Steffen Oeltze, Hartmut Schütze, Anne Maaß, Emrah Düzel, Bernhard Preim
2014 Informatik aktuell  
It is based on the interpolated contour of the manually segmented SRLM and its medial axis. We automatically compute the axis by combining Voronoi diagrams and methods from graph analysis.  ...  We evaluate our approach based on coronal T 2 * -weighted 7-Tesla MR images of 27 subjects.  ...  [4] proposed a semi-automatic measurement. The user first draws in the medial axis of the SRLM in all slices.  ... 
doi:10.1007/978-3-642-54111-7_50 dblp:conf/bildmed/OeltzeSMDP14 fatcat:obl57it56nchdcpp3i4rku3km4

Automated Hippocampal Subfield Segmentation at 7T MRI

L.E.M. Wisse, H.J. Kuijf, A.M. Honingh, H. Wang, J.B. Pluta, S.R. Das, D.A. Wolk, J.J.M. Zwanenburg, P.A. Yushkevich, M.I. Geerlings
2016 American Journal of Neuroradiology  
CONCLUSIONS: This work demonstrates the feasibility of using a computational technique to automatically label hippocampal subfields and the entorhinal cortex at 7T MRI, with a high accuracy for most subfields  ...  We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI.  ...  [14] [15] [16] Several manual segmentation protocols exist for 7T MRI, 5, 7, 17 and a semi automatic technique for measuring the thickness of hippocampal subfields and layers in the hippocampal body  ... 
doi:10.3174/ajnr.a4659 pmid:26846925 pmcid:PMC4907820 fatcat:mbva7kosgfgrlp43s5222jnuh4

Performance of semi-automated hippocampal subfield segmentation methods across ages in a pediatric sample

Margaret L. Schlichting, Michael L. Mack, Katharine F. Guarino, Alison R. Preston
2019 NeuroImage  
In a developmental sample of individuals spanning 6-30 years, we assessed the degree to which two semi-automated segmentation approaches-one approach based on Automated Segmentation of Hippocampal Subfields  ...  Moreover, manual segmentation requires some subjectivity and is not impervious to bias or error.  ...  Acknowledgments Many thanks to Jessica Church-Lang, Tammy Tran, and Amelia Wattenberger for assistance with participant recruitment, data collection, and helpful discussions.  ... 
doi:10.1016/j.neuroimage.2019.01.051 pmid:30731245 pmcid:PMC6524646 fatcat:hy7dp6dgpnegjlwwvohiyrtxny

A Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis Derived From Deep Learning-Based Segmentation of T1w-MRI

Michael Rebsamen, Piotr Radojewski, Richard McKinley, Mauricio Reyes, Roland Wiest, Christian Rummel
2022 Frontiers in Neurology  
sensitivity to quantify hippocampal sclerosis than atlas-based methods and derived shape features are more robust.  ...  learning-based segmentation of the hippocampus was the most sensitive to detecting HS.  ...  subfields (FS-SF) (14) and FSL-FIRST (15) , and contrasted the results to a deep learning (DL)based segmentation (16) .  ... 
doi:10.3389/fneur.2022.812432 pmid:35250818 pmcid:PMC8894898 fatcat:pefls3t7kngfvesejxxrxzjpri

Multi-Atlas Segmentation with Joint Label Fusion

Hongzhi Wang, J. W. Suh, S. R. Das, J. B. Pluta, C. Craige, P. A. Yushkevich
2013 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Multi-atlas segmentation is an effective approach for automatically labeling objects of interest in biomedical images.  ...  We validate our method in two medical image segmentation problems: hippocampus segmentation and hippocampus subfield segmentation in magnetic resonance (MR) images.  ...  Acknowledgements We thank Sussane Mueller and Michael Weiner for providing the images used in our hippocampal subfield segmentation experiments.  ... 
doi:10.1109/tpami.2012.143 pmid:22732662 pmcid:PMC3864549 fatcat:kidcxtml7ngihd6hojfarlgfr4

Optimization and validation of automated hippocampal subfield segmentation across the lifespan

Andrew R. Bender, Attila Keresztes, Nils C. Bodammer, Yee Lee Shing, Markus Werkle-Bergner, Ana M. Daugherty, Qijing Yu, Simone Kühn, Ulman Lindenberger, Naftali Raz
2017 Human Brain Mapping  
We evaluated the concurrent validity of an automated method for hippocampal subfields segmentation (automated segmentation of hippocampal subfields, ASHS; Yushkevich et al., 2015b) using a customized atlas  ...  , yielding ICC above 0.90 for all subfields and alleviating systematic bias.  ...  This atlas combination is then followed by a corrective learning function, which uses a machine learning approach to improve manual-automatic segmentation similarity based on a given number of manually  ... 
doi:10.1002/hbm.23891 pmid:29171108 fatcat:fe57ad3xvbdl5es7cshyowinpq

Hippocampal Segmentation in Brain MRI Images Using Machine Learning Methods: A Survey

PAN Yi, LIU Jin, TIAN Xu, LAN Wei, GUO Rui
2021 Chinese journal of electronics  
Next, brain hippocampal segmentation methods based on traditional machine learning and deep learning are described.  ...  With the development of machine learning, many innovative methods have been proposed to segment the hippocampus.  ...  Many of the MR sessions are accompanied by volumetric segmentation files produced by FreeSurfer. • Automatic Segmentation of Hippocampal Subfields (ASHS) This dataset was released with the ASHS software  ... 
doi:10.1049/cje.2021.06.002 fatcat:huj7qx4ajzghpj7jhwh7wzztoi

Comparison of semi-automated hippocampal subfield segmentation methods in a pediatric sample [article]

Margaret L Schlichting, Michael L Mack, Katharine F Guarino, Alison R Preston
2016 bioRxiv   pre-print
Moreover, manual segmentation requires some subjectivity and is not impervious to bias or error.  ...  Hippocampal Subfields (ASHS), to manual subfield delineation on each individual by a single expert rater.  ...  brain implemented using the Automated Segmentation of Hippocampal Subfields (ASHS) software (Paul A.  ... 
doi:10.1101/064303 fatcat:urqcbuk65relvojukps3vfjroy

Semantic Segmentation of Hippocampal Subregions With U-Net Architecture

Soraya Nasser, Moulkheir Naoui, Ghalem Belalem, Saïd Mahmoudi
2021 International Journal of E-Health and Medical Communications (IJEHMC)  
hippocampal sub-regions ( Hippocampus Segmentation Multi Class HSMC), these two networks inspire their architecture of the U-net model.  ...  The Automatic semantic segmentation of the hippocampus is an important area of research in which several convolutional neural networks (CNN) models have been used to detect the hippocampus from whole cerebral  ...  On the other hand, semi-automated segmentation approaches are more advanced, such as those based on deformable models and the use of atlases.  ... 
doi:10.4018/ijehmc.20211101.oa4 fatcat:nbtwfq2e7bhmtov3st2urpdgy4

A computational atlas of the hippocampal formation using ex vivo , ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI

Juan Eugenio Iglesias, Jean C. Augustinack, Khoa Nguyen, Christopher M. Player, Allison Player, Michelle Wright, Nicole Roy, Matthew P. Frosch, Ann C. McKee, Lawrence L. Wald, Bruce Fischl, Koen Van Leemput
2015 NeuroImage  
The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast  ...  The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference.  ...  This research was also supported by NIH grants P30-AG010129 and K01-AG030514, as well as the ADNI 2 add-on project "Hippocampal Subfield Volumetry" (ADNI 2-12-233036).  ... 
doi:10.1016/j.neuroimage.2015.04.042 pmid:25936807 pmcid:PMC4461537 fatcat:oksmsx6wdrccbazgzvutbrjtqa

Automatic segmentation of the hippocampus for preterm neonates from early-in-life to term-equivalent age

Ting Guo, Julie L. Winterburn, Jon Pipitone, Emma G. Duerden, Min Tae M. Park, Vann Chau, Kenneth J. Poskitt, Ruth E. Grunau, Anne Synnes, Steven P. Miller, M. Mallar Chakravarty
2015 NeuroImage: Clinical  
The present study focuses on the development and validation of an automatic segmentation protocol that is based on the MAGeT-Brain (Multiple Automatically Generated Templates) algorithm to delineate the  ...  These manual segmentations are considered the gold standard in assessing the automatic segmentations.  ...  Fig. 8 . 8 Comparison of manual hippocampal segmentations with MAGeT-Brain-based hippocampal segmentations on the 22 early-in-life images of very preterm-born infants.  ... 
doi:10.1016/j.nicl.2015.07.019 pmid:26740912 pmcid:PMC4561668 fatcat:upmc2zatgnbodb3sn3gaz64nqu

Nonlinear interaction between APOE ε 4 allele load and age in the hippocampal surface of cognitively intact individuals

Gerard Martí‐Juan, Gerard Sanroma‐Guell, Raffaele Cacciaglia, Carles Falcon, Grégory Operto, José Luis Molinuevo, Miguel Ángel González Ballester, Juan Domingo Gispert, Gemma Piella, The Alzheimer's Disease Neuroimaging Initiative, The ALFA Study
2020 Human Brain Mapping  
We segmented the hippocampus of the subjects with a multi-atlas-based approach, obtaining high-dimensional meshes that can be analyzed in a multivariate way.  ...  In this work we analyzed the impact of APOE ε4 gene dose and its association with age, on hippocampal shape assessed with multivariate surface analysis, in a ε4-enriched cohort of n = 479 cognitively healthy  ...  The hippocampus segmentations of the atlases, provided by ADNI, were computed using a semi-automatic hippocampal volumetry method (Hsu et al., 2002) .  ... 
doi:10.1002/hbm.25202 pmid:33017488 pmcid:PMC7721244 fatcat:qabc5wmjzzhrtk2olmpprwztqm

Amyloid-β and α-synuclein cerebrospinal fluid biomarkers and cognition in early Parkinson's disease

Ane Løvli Stav, Dag Aarsland, Krisztina Kunszt Johansen, Erik Hessen, Eirik Auning, Tormod Fladby
2015 Parkinsonism & Related Disorders  
hippocampal volumes using hippocampal subfield segmentation with FreeSurfer compared to Aβ-PET negative participants, suggesting an association between hippocampal subfield atrophy and Aβ plaques in preclinical  ...  One study compared automated hippocampal subfield segmentation using FreeSurfer on lower resolution 3 T MRI with manual segmentation on high-resolution 3 T MRI (244).  ...  PD patients had smaller volumes of total hippocampus, presubiculum, subiculum, CA2-3, CA4-DG, and hippocampal tail compared with normal controls (NCs).  ... 
doi:10.1016/j.parkreldis.2015.04.027 pmid:25971633 fatcat:waisjlasjvhdrlec6tkf6fcevm

Medical imaging diagnosis of early Alzheimer rsquo s disease

Ayman El-Baz
2018 Frontiers in Bioscience  
(42) focused on the automatic segmentation of the hippocampal subfields due to their relation to the early pathology of AD.  ...  References Table 2 . 2 The MRI studies based on Hippocampus Ref. 43 Approach details Goal Segmentation (multi-atlas image segmentation with ELM based bias detection and correction technique)  ...  Dependency upon the enrolled data also represents a source of limitations in the context of applying computerized methods/techniques with AD.  ... 
doi:10.2741/4612 pmid:28930568 fatcat:6f5gzcdyireuro3ylaswz2p734

Theta- and gamma-band oscillatory uncoupling in the macaque hippocampus [article]

Saman Abbaspoor, Ahmed Hussin, Kari L Hoffman
2022 bioRxiv   pre-print
Nested hippocampal oscillations in the rodent gives rise to temporal coding that may underlie learning, memory, and decision making.  ...  Moreover, delta/theta (3-8 Hz) amplitude was strongest when beta2/slow gamma (20-35 Hz) amplitude was weakest, though the low frequencies coupled with higher, ripple frequencies (60-150 Hz).  ...  Spike sorting was performed semi-automatically using KlustaKwik based on wave shape, principal components, energy, and peak/valley across channels.  ... 
doi:10.1101/2021.12.30.474585 fatcat:bzow3572ybhg3jjryybvfaxybu
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