Automated Segmentation of Hippocampal Subfields in Drug-Naïve Patients with Alzheimer Disease
Open accessAbstract
BACKGROUND AND PURPOSE: Although a few automated hippocampal subfield segmentation methods have been developed, there is no study on the effects of the diagnosis of Alzheimer disease on the hippocampal subfield volume with in vivo MR imaging. The aim of this study was to investigate hippocampal subfield volume differences between drug-naïve subjects with AD and healthy elderly controls by using an automated hippocampal subfield segmentation technique. MATERIALS AND METHODS: Thirty-one drug-naïve subjects with AD and 33 group-matched healthy control subjects underwent 3T MR imaging, and hippocampal subfield volume was measured and compared between the groups. RESULTS: Subjects with AD had significantly smaller volumes of the presubiculum, subiculum, CA2-3, and CA4 DG compared with healthy subjects (uncorrected, P<.001). In addition, we found significant positive correlations between the presubiculum and the subicular volumes and the MMSE-K and the CERAD-K verbal delayed recall scores in the AD group. CONCLUSIONS: We are unaware of previous imaging studies of automated hippocampal subfield segmentation in AD. These structural changes in the hippocampal presubiculum, subiculum, and CA2-3 might be at the core of underlying neurobiologic mechanisms of hippocampal dysfunction and their relevance to verbal delayed recall impairments in AD.
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Previous neuroimaging studies obtained contrasting data regarding the pattern of hippocampal subfield atrophy in AD patients.
“Previous neuroimaging studies obtained contrasting data regarding the pattern of hippocampal subfield atrophy in AD patients.”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [31]
Normal volume of the CA1 subfield was reported by Lim et al. and by Kerchner et al.
“Normal volume of the CA1 subfield was reported by Lim et al. [31], who used the same automated segmentation protocol used in the present study, and by Kerchner et al. [32], who inferred volume by measuring the thickness of the CA1 subfield”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [31]
In fully developed AD, all studies agree that the subiculum and the presubiculum show atrophic changes.
“all studies agree that the subiculum and the presubiculum show atrophic changes”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [31]
In fully developed AD, studies differ as to the pattern of volume reduction in Ammon's horn subfields.
“differ as to the pattern of the volume reduction in Ammon's horn subfields”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [31]
The studies by Lim et al. and Kerchner et al. included patients whose disease severity was similar to that of the present study's patients.
“both of the aforementioned studies included patients whose disease severity was similar to that of our patients (as indicated by MMSE and CDR scores).”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [31]
The volume of the CA3 and CA4 subfields was found in the normal range in most studies using manual segmentation and 3D surface reconstruction but was invariably atrophic in studies based on automated segmentation procedures.
“Conversely, the volume of the CA3 and CA4 subfields was found in the normal range in most of the studies that used manual segmentation [34], [35] and 3D surface reconstruction and shape analysis [36] but was invariably atrophic in studies based on automated segmentation procedures [31], [33].”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [31]
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Cites
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915 · see citing works
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123 · see citing works
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910 · see citing works
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882 · see citing works
Measuring the thickness of the human cerebral cortex from magnetic resonance images
Fischl, B. R., & Dale, A. M. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200033797 · Cited by 5,789 · see citing works
The Medial Temporal Lobe Memory System
Squire, L. R., & Zola-Morgan, S. (1991) · Science · doi:10.1126/science.1896849 · Cited by 3,282 · see citing works
Regional Brain Changes in Aging Healthy Adults: General Trends, Individual Differences and Modifiers
Raz, N., Lindenberger, U., Rodrigue, K. M., Kennedy, K. M., Head, D., Williamson, A., Dahle, C., Gerstorf, D., & Acker, J. D. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhi044 · Cited by 2,875 · see citing works
Lee, J. H., Lee, K. U., Lee, D. Y., Kim, K. W., Jhoo, J. H., Kim, J. H., Lee, K. H., Kim, S. Y., Han, S., & Woo, J. I. (2002) · The Journals of Gerontology Series B · doi:10.1093/geronb/57.1.p47 · Cited by 774 · see citing works
Duvernoy, H. M., Cattin, F., & Risold, P. (2013) · Springer eBooks · doi:10.1007/978-3-642-33603-4 · Cited by 567 · see citing works
Automated segmentation of hippocampal subfields from ultra‐high resolution in vivo MRI
Van Leemput, K., Bakkour, A., Benner, T., Wiggins, G., Wald, L. L., Augustinack, J., Dickerson, B. C., Golland, P., & Fischl, B. (2009) · Hippocampus · doi:10.1002/hipo.20615 · Cited by 405 · see citing works
Computer-assisted imaging to assess brain structure in healthy and diseased brains
Ashburner, J., Csernansk, J. G., Davatzikos, C., Fox, N. C., Frisoni, G. B., & Thompson, P. M. (2003) · The Lancet Neurology · doi:10.1016/s1474-4422(03)00304-1 · Cited by 371 · see citing works
Hippocampal atrophy patterns in mild cognitive impairment and Alzheimer's disease
Mueller, S. G., Schuff, N., Yaffe, K., Madison, C., Miller, B., & Weiner, M. W. (2010) · Human Brain Mapping · doi:10.1002/hbm.20934 · Cited by 361 · see citing works
The Human Hippocampus: Functional Anatomy, Vascularization and Serial Sections with MRI
Duvernoy, H. M. (2005) · doi:10.1007/b138576 · Cited by 350 · see citing works
Regional cerebral cortical thinning in bipolar disorder
Lyoo, I. K., Sung, Y. H., Dager, S. R., Friedman, S. D., Lee, J., Kim, S. J., Kim, N., Dünner, D. L., & Renshaw, P. F. (2006) · Bipolar Disorders · doi:10.1111/j.1399-5618.2006.00284.x · Cited by 300 · see citing works
Selective effect of age, Apo e4, and Alzheimer's disease on hippocampal subfields
Mueller, S. G., & Weiner, M. W. (2009) · Hippocampus · doi:10.1002/hipo.20614 · Cited by 248 · see citing works
Málková, L., & Mishkin, M. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-05-01956.2003 · Cited by 239 · see citing works
Nearly automatic segmentation of hippocampal subfields in in vivo focal T2-weighted MRI
Yushkevich, P. A., Wang, H., Pluta, J. B., Das, S. R., Craige, C. P., Avants, B., Weiner, M. W., & Mueller, S. G. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.040 · Cited by 231 · see citing works
Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment
Costafreda, S. G., Dinov, I. D., Tu, Z., Shi, Y., Liu, C.-Y., Kłoszewska, I., Mecocci, P., Soininen, H. S., Tsolaki, M., Vellas, B. J., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.050 · Cited by 213 · see citing works
Park, J., & Kwon, Y. C. (1990) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.930050606 · Cited by 177 · see citing works
Braak, E., & Braak, H. (1997) · Acta Neuropathologica · doi:10.1007/s004010050622 · Cited by 143 · see citing works
In vivo neuropathology of the hippocampal formation in AD: a radial mapping MR-based study
Frisoni, G. B., Sabattoli, F., Lee, A. D., Dutton, R. A., Toga, A. W., & Thompson, P. M. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.03.015 · Cited by 128 · see citing works
Hippocampal Shape Analysis of Alzheimer Disease Based on Machine Learning Methods
Li, S., Shi, F., Pu, F., Li, X., Jiang, T., Xie, S., & Wang, Y. (2007) · American Journal of Neuroradiology · doi:10.3174/ajnr.a0620 · Cited by 125 · see citing works
Mild Cognitive Impairment: Differential Atrophy in the Hippocampal Subfields
Hanseeuw, B. J., Van Leemput, K., Kavec, M., Grandin, C., Seron, X., & Ivanoiu, A. (2011) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2589 · Cited by 110 · see citing works
Wisniewski, H. M., Sadowski, M., Jakubowska-Sadowswka, K., Tarnawski, M., & Wegiel, J. (1998) · Journal of Neuropathology and Experimental Neurology · doi:10.1097/00005072-199807000-00004 · Cited by 71 · see citing works
Hippocampal atrophy secondary to entorhinal cortical degeneration in Alzheimer-type dementia
Mizutani, T., & Kasahara, M. (1997) · Neuroscience Letters · doi:10.1016/s0304-3940(97)13365-1 · Cited by 53 · see citing works
Donepezil Treatment and Changes in Hippocampal Structure in Very Mild Alzheimer Disease
Wang, L., Harms, M. P., Staggs, J. M., Xiong, C., Morris, J. C., Csernansky, J. G., & Galvin, J. E. (2010) · Archives of Neurology · doi:10.1001/archneurol.2009.292 · Cited by 24 · see citing works
?imi?, G., Kostovi?, I., Winblad, B., & Bogdanovi?, N. (1997) · The Journal of Comparative Neurology · doi:10.1002/(sici)1096-9861(19970324)379:4
Flagged first, then by citations
Cited by
Sorted by citations
Structural imaging of hippocampal subfields in healthy aging and Alzheimer’s disease
de Florès, R., Joie, R. L., & Chételat, G. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.08.033 · Cited by 363 · see citing works
Haukvik, U. K., Tamnes, C. K., Söderman, E., & Agartz, I. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.08.012 · Cited by 220 · see citing works
In Vivo Hippocampal Subfield Volumes in Schizophrenia and Bipolar Disorder
Haukvik, U. K., Westlye, L. T., Mørch-Johnsen, L. E., Jørgensen, K. N., Lange, E. H., Dale, A. M., Melle, I. S., Andreassen, O. A., & Agartz, I. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.06.020 · Cited by 186 · see citing works
Hippocampal subfield volumes at 7T in early Alzheimer's disease and normal aging
Wisse, L. E. M., Biessels, G. J., Heringa, S. M., Kuijf, H. J., Koek, D., Luijten, P. R., & Geerlings, M. I. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.02.021 · Cited by 171 · see citing works
Prevedello, L. M. S., Halabi, S. S., Shih, G., Wu, C. C., Kohli, M. D., Chokshi, F. H., Erickson, B. J., Kalpathy–Cramer, J., Andriole, K. P., & Flanders, A. E. (2019) · Radiology Artificial Intelligence · doi:10.1148/ryai.2019180031 · Cited by 175 · see citing works
Carlesimo, G. A., Piras, F., Orfei, M. D., Iorio, M., Caltagirone, C., & Spalletta, G. (2015) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1016/j.dadm.2014.12.001 · Cited by 159 · see citing works
A Critical Appraisal of the Hippocampal Subfield Segmentation Package in FreeSurfer
Wisse, L. E. M., Biessels, G. J., & Geerlings, M. I. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00261 · Cited by 145 · see citing works
Effects of age and Alzheimer's disease on hippocampal subfields
de Florès, R., Joie, R. L., Landeau, B., Perrotin, A., Mézenge, F., Sayette, V. D. L., Eustache, F., Desgranges, B., & Chételat, G. (2014) · Human Brain Mapping · doi:10.1002/hbm.22640 · Cited by 142 · see citing works
Sämann, P. G., Iglesias, J. E., Gutman, B. A., Grotegerd, D., Leenings, R., Flint, C., Dannlowski, U., Clarke‐Rubright, E. K., Morey, R. A., van Erp, T. G. M., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25326 · Cited by 135 · see citing works
Heritability and reliability of automatically segmented human hippocampal formation subregions
Whelan, C. D., Hibar, D. P., van Velzen, L. S., Zannas, A. S., Carrillo‐Roa, T., McMahon, K. L., Prasad, G., Kelly, S., Faskowitz, J., de Zubicaray, G. I., et al. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.039 · Cited by 118 · see citing works
Foo, H., Mak, E., Chander, R. J., Ng, A. Y. T., Au, W. L., Sitoh, Y. Y., Tan, L. C. S., & Kandiah, N. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.12.008 · Cited by 116 · see citing works
Sarica, A., Vasta, R., Novellino, F., Vaccaro, M. G., Cerasa, A., Quattrone, A., & Initiative, T. A. D. N. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00576 · Cited by 116 · see citing works
Zheng, F., Cui, D., Zhang, L., Zhang, S., Zhao, Y., Liu, X., Liu, C., Li, Z., Zhang, D., Shi, L., et al. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00320 · Cited by 90 · see citing works
Amaral, R. S. C., Park, M. T. M., Devenyi, G. A., Lynn, V., Pipitone, J., Winterburn, J. L., Chavez, S., Schira, M. M., Lobaugh, N. J., Voineskos, A. N., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.10.027 · Cited by 83 · see citing works
Mak, E., Su, L., Williams, G. B., Watson, R., Firbank, M., Blamire, A., & O’Brien, J. (2016) · The American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2015.06.006 · Cited by 79 · see citing works
Schoene‐Bake, J., Keller, S. S., Niehusmann, P., Volmering, E., Elger, C. E., Deppe, M., & Weber, B. (2014) · Human Brain Mapping · doi:10.1002/hbm.22506 · Cited by 78 · see citing works
Fillenbaum, G. G., & Mohs, R. C. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230026 · Cited by 73 · see citing works
Hippocampal subfield volumetry in patients with subcortical vascular mild cognitive impairment
Li, X., Li, D., Li, Q., Li, Y., Li, K., Li, S., & Han, Y. (2016) · Scientific Reports · doi:10.1038/srep20873 · Cited by 68 · see citing works
Hippocampal subfield analysis in medication-naïve female patients with major depressive disorder
Han, K.-M., Won, E., Sim, Y., & Tae, W.-S. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.01.019 · Cited by 63 · see citing works
Ota, M., Sato, N., Hidese, S., Teraishi, T., Maikusa, N., Matsuda, H., Hattori, K., & Kunugi, H. (2016) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2016.11.002 · Cited by 59 · see citing works
Zhang, Y.-W., Zhang, J., Liu, C., Wei, P., Zhang, X., Yuan, Q., Yin, X., Wei, L., Cui, J., & Wang, J. (2015) · Chinese Medical Journal · doi:10.4103/0366-6999.151082 · Cited by 57 · see citing works
de Florès, R., Berron, D., Ding, S., Ittyerah, R., Pluta, J. B., Xie, L., Adler, D. H., Robinson, J. L., Schuck, T., Trojanowski, J. Q., et al. (2019) · Hippocampus · doi:10.1002/hipo.23172 · Cited by 53 · see citing works
Zhang, J., Xie, L., Cheng, C., Liu, Y., Zhang, X., Wang, H., Hu, J., Yu, H., & Xu, J. (2023) · Brain Imaging and Behavior · doi:10.1007/s11682-023-00804-3 · Cited by 43 · see citing works
Györfi, O., Nagy, H., Bokor, M., Moustafa, A. A., Rosenzweig, I., Kelemen, O., & Kéri, S. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00084 · Cited by 40 · see citing works
The neuropsychological spectrum of anti-LGI1 antibody mediated autoimmune encephalitis
Griffith, S. P., Malpas, C. B., Alpitsis, R., O'Brien, T. J., & Monif, M. (2020) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2020.577271 · Cited by 37 · see citing works
The relationship between hippocampal subfield volumes and autobiographical memory persistence
Barry, D. N., Clark, I. A., & Maguire, E. A. (2020) · Hippocampus · doi:10.1002/hipo.23293 · Cited by 36 · see citing works
Reduced Hippocampal Subfield Volume in Schizophrenia and Clinical High-Risk State for Psychosis
Sasabayashi, D., Yoshimura, R., Takahashi, T., Takayanagi, Y., Nishiyama, S., Higuchi, Y., Mizukami, Y., Furuichi, A., Kido, M., Nakamura, M., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.642048 · Cited by 36 · see citing works
Ben-Zion, Z., Korem, N., Fine, N. B., Katz, S., Siddhanta, M., Funaro, M., Duek, O., Spiller, T., Danböck, S. K., Levy, I., et al. (2023) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2023.07.001 · Cited by 28 · see citing works
Hirjak, D., Wolf, R. C., Remmele, B., Seidl, U., Thomann, A., Kubera, K. M., Schröder, J., Maier-Hein, K. H., & Thomann, P. A. (2017) · Hippocampus · doi:10.1002/hipo.22726 · Cited by 25 · see citing works
Choi, E.-J., Son, Y., Noh, Y., Lee, H., Kim, Y.-B., & Park, K. H. (2018) · Journal of Clinical Neurology · doi:10.3988/jcn.2018.14.2.158 · Cited by 25 · see citing works
Differential Atrophy in the Hippocampal Subfield Volumes in Four Types of Mild Dementia
Huang, L., Chen, K., Hu, X., & Guo, Q. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00699 · Cited by 24 · see citing works
Bouwman, M. M. A., Frigerio, I., Lin, C., Reijner, N., van de Berg, W. D. J., & Jonkman, L. E. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01768-w · Cited by 23 · see citing works
Kang, D. W., Lim, H. K., Joo, S. H., Lee, N. R., & Lee, C. U. (2018) · Neuropsychiatric Disease and Treatment · doi:10.2147/ndt.s151659 · Cited by 21 · see citing works
Self-citationChoi, W. H., Jung, W. S., Um, Y. H., Lee, C. U., Park, Y. H., & Lim, H. K. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.08.070 · Cited by 20 · see citing works
Self-citationAge‐related differences in hippocampal subfield volumes across the human lifespan: A meta‐analysis
Homayouni, R., Canada, K. L., Saifullah, S., Foster, D. J., Thill, C., Raz, N., Daugherty, A. M., & Ofen, N. (2023) · Hippocampus · doi:10.1002/hipo.23582 · Cited by 22 · see citing works
Hippocampal volume asymmetry in Alzheimer disease: A systematic review and meta-analysis
Pusparani, Y., Lin, C., Jan, Y., Lin, F., Liau, B.-Y., Alex, J. S. R., Aparajeeta, J., Chao, W.-H., & Lung, C.-W. (2025) · Medicine · doi:10.1097/md.0000000000041662 · Cited by 18 · see citing works
Association between subfield volumes of the medial temporal lobe and cognitive assessments
Ogawa, M., Sone, D., Beheshti, I., Maikusa, N., Okita, K., Takano, H., & Matsuda, H. (2019) · Heliyon · doi:10.1016/j.heliyon.2019.e01828 · Cited by 18 · see citing works
Ji, E. K., Wang, H. H., Jung, S. J., Lee, K. B., Kim, J. S., Hong, B. Y., & Lim, S. H. (2019) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2019.08.031 · Cited by 17 · see citing works
Hippocampal subfield volumes are associated with verbal memory after first‐ever ischemic stroke
Khlif, M. S., Bird, L., Restrepo, C., Khan, W., Werden, E., Egorova, N., & Brodtmann, A. G. (2021) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12195 · Cited by 16 · see citing works
Gertje, E. C., Pluta, J. B., Das, S. R., Mancuso, L., Kliot, D., Yushkevich, P. A., & Wolk, D. A. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160014 · Cited by 11 · see citing works
Chen, L., Luo, T., Lv, F., Shi, D., Qiu, J., Li, Q., Fang, W., Peng, J., Li, Y., Zhang, Z., et al. (2015) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-015-0654-5 · Cited by 12 · see citing works
Hirjak, D., Sambataro, F., Remmele, B., Kubera, K. M., Schröder, J., Seidl, U., Thomann, A., Maier-Hein, K. H., Wolf, R. C., & Thomann, P. A. (2017) · The World Journal of Biological Psychiatry · doi:10.1080/15622975.2017.1355474 · Cited by 10 · see citing works
Cremona, S., Zago, L., Mellet, E., Petit, L., Laurent, A., Pepe, A., Tsuchida, A., Beguedou, N., Joliot, M., Tzourio, C., et al. (2021) · Human Brain Mapping · doi:10.1002/hbm.25614 · Cited by 6 · see citing works
The Changes for Strength of Oropharyngeal Muscles in Patients with Dementia and Dysphagia
Ji, E. K., Wang, H. H., Jung, S. J., Lee, K. B., Kim, J. S., Hong, B. Y., Kim, T., & Lim, S. H. (2019) · Brain & Neurorehabilitation · doi:10.12786/bn.2019.12.e12 · Cited by 8 · see citing works
Busatto, G. F., Duran, F., Squarzoni, P., Coutinho, A. M., Rosa, P. G. P., Torralbo, L., Pachi, C. G. D. F., da Costa, N. A., Porto, F. H. D. G., Carvalho, C. L., et al. (2020) · Journal of Neuroscience Research · doi:10.1002/jnr.24739 · Cited by 7 · see citing works
Atrophy of Ipsilesional Hippocampal Subfields Vary Over First Year After Ischemic Stroke
Khlif, M. S., Werden, E., Bird, L., Egorova, N., & Brodtmann, A. G. (2021) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.28009 · Cited by 8 · see citing works
de Florès, R., Joie, R. L., Landeau, B., Perrotin, A., Mézenge, F., Sayette, V. D. L., Eustache, F., Desgranges, B., & Chételat, G. (2014) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2014.05.098 · Cited by 1 · see citing works
Challenges in Accurately Using Artificial Intelligence and Machine Learning in Biomedical Imaging
Sharma, M., Goswami, B., Goswami, N., Mahanta, S., & Singh, Y. J. (2024) · Biological and medical physics, biomedical engineering · doi:10.1007/978-981-97-5345-1_3 · Cited by 2 · see citing works
Abdolalizadeh, A., Moradi, K., Ohadi, M. A. D., Mirfazeli, F. S., & Rajimehr, R. (2023) · Scientific Reports · doi:10.1038/s41598-023-33198-9 · Cited by 1 · see citing works
Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans
N., A. B., Li, K., Honnorat, N., Rashid, T., Wang, D., Li, J.-Q., Fadaee, E., Charisis, S., Walker, J., Richardson, T., et al. (2025) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2024.110359
Hsu, Y., Huang, S., Kuo, L., Yang, J., & Tu, M.-C. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251351612
Wen, Y., Quinsten, A. S., Schmidt, C. S., Bojahr, C., Kohnke, J., Arzideh, K., Warmer, S., Blex, S., Jacoby, A.-C., Eberts, M., et al. (2026) · JMIR Medical Informatics · doi:10.2196/93018
- Authors
- Lim, H. K., Hong, S. C., Jung, W. S., Ahn, K. J., Won, W. Y., Hahn, C., Kim, I. S., & Lee, C. U.
- Affiliations
- The Catholic University of Korea St. Vincent's Hospital (KR)
- St. Paul's Hospital (KR)
- The Catholic University of Korea Seoul St. Mary's Hospital (KR)
- Venue
- American Journal of Neuroradiology
- Published
- 2012-10-04
- Volume
- 34
- Issue
- 4
- Pages
- 747-751
- ISSN
- 0195-6108 (ISSN-L)
- 1936-959X
- PMC
- PMC7964501
- OpenAlex
- W2162771276
- Cited by
- 52
- References
- 27
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 1 · 2023: 5 · 2021: 4 · 2020: 5 · 2019: 5 · 2018: 5 · 2017: 3 · 2016: 7 · 2015: 6 · 2014: 6
- FWCI
- 2.73
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- American Journal of Neuroradiology (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- Alzheimer's disease, hippocampal subfields, automatic segmentation, drug-naive patients, presubiculum, subiculum, CA2/3, dentate gyrus, hippocampal volume, hippocampal dysfunction
- MeSH terms
- Aged, Aged, 80 and over, Aging, Alzheimer Disease, Female, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Mental Recall, Dentate Gyrus, CA2 Region, Hippocampal, CA3 Region, Hippocampal
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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