ASHS: Automatic Segmentation of Hippocampal Subfields Releases

Penn Memory Center 3T ASHS Atlas for T1-weighted MRI February 2025 Release with Amygdala and Anterior MTL

yushkevich@www.nitrc.org (Paul Yushkevich) — Fri, 21 Feb 2025 18:42:00 GMT

This atlas extends T1-ASHS PMC atlas with more anterior regions and the amygdala label, as described in Sadeghpour et al., 2025: <a href="https://doi.org/10.1101/2025.02.11.637506">https://doi.org/10.1101/2025.02.11.637506</a>

Penn Memory Center 3T ASHS Atlas for T1-weighted MRI July 2023 Release with White Matter Label

yushkevich@www.nitrc.org (Paul Yushkevich) — Mon, 17 Jul 2023 13:24:00 GMT

This version of the atlas includes a white matter label generated by Yue Li at the University of Pennsylvania. It can be used for surface-based group level analysis of medial temporal lobe structures using the new CrASHS pipeline (https://github.com/pyushkevich/crashs). 
Please reference our AAIC 2023 abstract:
Paul A. Yushkevich, Long Xie, Laura E. M. Wisse, Mengjin Dong, Sadhana Ravikumar, Ranjit Ittyerah,  Robin de Flores, Sandhitsu R. Das, David A. Wolk for the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Mapping Medial Temporal Lobe Longitudinal Change in Preclinical Alzheimer’s Disease, 2023 Alzheimer's Association International Conference (AAIC 2023).

Penn ABC-3T ASHS Atlas for T2-weighted MRI (Berron'17 protocol) 1.0.0

yushkevich@www.nitrc.org (Paul Yushkevich) — Mon, 28 Nov 2022 18:16:00 GMT

IKND Magdeburg Young Adult 7T Atlas 1.0.0

yushkevich@www.nitrc.org (Paul Yushkevich) — Fri, 22 Mar 2019 13:49:00 GMT

fast-ashs v2.0.0 (July 2018)

longxie@www.nitrc.org (Long Xie) — Fri, 20 Jul 2018 20:59:00 GMT

* Added support for non-local-mean denoising and upsampling as preprocessing steps

* User can specify additional arguments for GNU parallel

Penn Memory Center 3T ASHS Atlas for T1-weighted MRI Initial release July 2018

longxie@www.nitrc.org (Long Xie) — Fri, 20 Jul 2018 20:30:00 GMT

This is an atlas set that can be used with ASHS-FAST VERSION 2.0 (July 2018) OR LATER software to perform automatic segmentation of medial temporal lobe substructures in 3 Tesla T1-weighted MRI (MPRAGE) scans explicitly accounting for the dura mater (which has similar intensity as gray matter in T1-weighted MRI that could confound automatic segmentation).

This atlas set was constructed from MRI scans acquired in research studies conducted at the Penn Memory Center at the University of Pennsylvania by David A. Wolk, Paul A. Yushkevich and colleagues. The scans have been segmented
manually by Long Xie and Laura Wisse based on the manual segmentations in the Penn Memory Center 3T ASHS Atlas for T2-weighted MRI (by John Pluta).

The atlas contains segmented scans of 29 older adults, 14 meeting the Peterson criteria for amnestic mild cognitive impairment, and 15 controls. Scans were acquired at 3 Tesla. The whole brain T1-weighted scans are at 1.0x1.0x1.0 mm3 resolution. The labels include anterior/posterior hippocampus, entorhinal cortex (ERC), perirhinal cortex (further divided into Brodmann areas 35 and 36, or BA35 and BA36), and parahippocampal cortex (PHC).

Any use in publication should cite

XieL., WisseE.M.L., ManjonV.J. Wang H., Das, S.R., Wolk A.D., Yushkevich A.P. (2016). Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-weighted MRI. Athens, Greece. Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016(pp. 564-571). Springer International Publishing.

Please see these papers for details on the dataset.

Princeton Young Adult 3T ASHS Atlas 1.0.0

yushkevich@www.nitrc.org (Paul Yushkevich) — Tue, 08 May 2018 4:00:00 GMT

This is an atlas set that can be used with ASHS software to perform automatic segmentation.

This atlas set was constructed from MRI scans and manual segmentations graciously shared by Mariam Aly, Nicholas Hindy, Nicholas Turk-Browne
and colleagues at the Department of Psychology, Princeton University. The atlas is described in

[list][*]Hindy, N. C., Ng, F. Y., & Turk-Browne, N. B. (2016). Linking pattern completion in the hippocampus to predictive coding in visual cortex. Nature Neuroscience, 19(5), 665–667.[/list]
Copyright (C) 2014 Mariam Aly, Nicholas Hindy, Nicholas Turk-Browne

The atlas contains segmented scans of 24 young healthy adults acquired at 3 Tesla. The T2-weighted scans are at 0.4x0.4x1.5mm3 resolution. The
manual segmentations by Mariam Aly include seven labels, including hippocampal subfields traced along the full length of the hippocampus, and extrahippocampal cortical structures (ERC/PRC/PHC).

fast-ashs v1.0.0 (September 2017)

yushkevich@www.nitrc.org (Paul Yushkevich) — Fri, 15 Sep 2017 14:49:00 GMT

This is the latest ASHS release. Starting with September 2017, ASHS will use numerical versions. This is the official [b]1.0.0[/b] release.

This release will only work with atlases marked compatible with the 1.0 release. However, you can upgrade your own atlases using the ashs_atlas_update script in the bin directory. For best performance, we do recommend rebuilding your custom atlases.

Penn Temporal Lobe Epilepsy T1-MRI Whole Hippocampus ASHS Atlas ASHS 1.0 Compatible Atlas

yushkevich@www.nitrc.org (Paul Yushkevich) — Fri, 15 Sep 2017 16:04:00 GMT

This atlas can be used for segmentation of the whole hippocampus using the HarP protocol (http://www.hippocampal-protocol.net/SOPs/index.php) in 3 Tesla T1-weighted MRI scans. The atlas is constructed from a set of normal controls from a study of temporal lobe epilepsy (TLE) and has been evaluated for the purposes of segmenting the hippocampus in TLE patients, yielding good accuracy (average Dice of 0.85 on the left, 0.86 on the right, relative to manual segmentation). The data for this study was collected at the Penn Epilepsy Center.

UMC Utrecht 7T ASHS Atlas ASHS 1.0 Compatible Atlas

yushkevich@www.nitrc.org (Paul Yushkevich) — Fri, 15 Sep 2017 16:12:00 GMT

This is an atlas set that can be used with ASHS VERSION 1.0 (September 2017) OR LATER software to perform automatic segmentation of hippocampal subfields in 7 Tesla MRI scans.

This atlas set was constructed from 7 Tesla MRI scans acquired in the PREDICT-MR study conducted at UMC Utrecht. The scans have been segmented manually by L.E.M. Wisse.

Copyright (C) 2016 Wisse, L.E.M., Kuijf, H.J., Honingh, A.M., Wang, H., Pluta, J.B., Das, S.R., Wolk, D.A., Zwanenburg, J.J.M., Yushkevich, P.A. and Geerlings, M.I.

The atlas contains segmented scans of 26 older adults from the PREDICT-MR study aimed to investigate determinants and consequences of brain changes on MRI in general practice attendees. Scans were acquired at 7 Tesla. The T2-weighted scans are at 0.35x0.35x0.35mm3 resolution (interpolated from 0.7x0.7x0.7 native resolution). The manual segmentations include several labels, including hippocampal subfields traced along the full length of the hippocampus, and the ERC. Scans have been face-stripped and are de-identified.

Any use in publication should cite

Wisse, L.E.M., Kuijf, H.J., Honingh, A.M., Wang, H., Pluta, J.B., Das, S.R., Wolk, D.A., Zwanenburg, J.J.M., Yushkevich, P.A. and Geerlings, M.I., 2016. Automated Hippocampal Subfield Segmentation at 7T MRI. American Journal of Neuroradiology.

and space permitting, please cite

Yushkevich, P.A., Pluta, J.B., Wang, H., Xie, L., Ding, S.L., Gertje, E.C., Mancuso, L., Kliot, D., Das, S.R. and Wolk, D.A., 2015. Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment. Human brain mapping, 36(1), pp.258-287.

Please see these papers for details on the dataset.