Alignment of Tractography Streamlines using Deformation Transfer via\n Parallel Transport Article Swipe
Andrew Lizarraga
,
David Lee
,
Antoni Kubicki
,
Ashish Sahib
,
Elvis Nunez
,
Katherine L. Narr
,
Shantanu H. Joshi
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2108.03697
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2108.03697
We present a geometric framework for aligning white matter fiber tracts. By\nregistering fiber tracts between brains, one expects to see overlap of\nanatomical structures that often provide meaningful comparisons across\nsubjects. However, the geometry of white matter tracts is highly heterogeneous,\nand finding direct tract-correspondence across multiple individuals remains a\nchallenging problem. We present a novel deformation metric between tracts that\nallows one to compare tracts while simultaneously obtaining a registration. To\naccomplish this, fiber tracts are represented by an intrinsic mean along with\nthe deformation fields represented by tangent vectors from the mean. In this\nsetting, one can determine a parallel transport between tracts and then\nregister corresponding tangent vectors. We present the results of bundle\nalignment on a population of 43 healthy adult subjects.\n
Related Topics
Concepts
Fiber tract
Tangent
Tractography
Metric (unit)
Parallel transport
Streamlines, streaklines, and pathlines
Diffusion MRI
Artificial intelligence
Segmentation
Landmark
Fiber bundle
White matter
Deformation (meteorology)
Geometry
Computer science
Fiber
Anatomy
Mathematics
Physics
Biology
Medicine
Magnetic resonance imaging
Radiology
Materials science
Composite material
Meteorology
Economics
Operations management
Thermodynamics
Metadata
- Type
- preprint
- Landing Page
- http://arxiv.org/abs/2108.03697
- https://arxiv.org/pdf/2108.03697
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4287027286
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4287027286Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2108.03697Digital Object Identifier
- Title
-
Alignment of Tractography Streamlines using Deformation Transfer via\n Parallel TransportWork title
- Type
-
preprintOpenAlex work type
- Publication year
-
2021Year of publication
- Publication date
-
2021-08-08Full publication date if available
- Authors
-
Andrew Lizarraga, David Lee, Antoni Kubicki, Ashish Sahib, Elvis Nunez, Katherine L. Narr, Shantanu H. JoshiList of authors in order
- Landing page
-
https://arxiv.org/abs/2108.03697Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2108.03697Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2108.03697Direct OA link when available
- Concepts
-
Fiber tract, Tangent, Tractography, Metric (unit), Parallel transport, Streamlines, streaklines, and pathlines, Diffusion MRI, Artificial intelligence, Segmentation, Landmark, Fiber bundle, White matter, Deformation (meteorology), Geometry, Computer science, Fiber, Anatomy, Mathematics, Physics, Biology, Medicine, Magnetic resonance imaging, Radiology, Materials science, Composite material, Meteorology, Economics, Operations management, ThermodynamicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4287027286 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2108.03697 |
| ids.openalex | https://openalex.org/W4287027286 |
| fwci | 0.0 |
| type | preprint |
| title | Alignment of Tractography Streamlines using Deformation Transfer via\n Parallel Transport |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11304 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9998000264167786 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2741 |
| topics[0].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[0].display_name | Advanced Neuroimaging Techniques and Applications |
| topics[1].id | https://openalex.org/T10052 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9714000225067139 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Medical Image Segmentation Techniques |
| topics[2].id | https://openalex.org/T10378 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9395999908447266 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2741 |
| topics[2].subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| topics[2].display_name | Advanced MRI Techniques and Applications |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2993925342 |
| concepts[0].level | 4 |
| concepts[0].score | 0.7442804574966431 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q28457374 |
| concepts[0].display_name | Fiber tract |
| concepts[1].id | https://openalex.org/C138187205 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6771615743637085 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q131251 |
| concepts[1].display_name | Tangent |
| concepts[2].id | https://openalex.org/C84787856 |
| concepts[2].level | 4 |
| concepts[2].score | 0.6400036811828613 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q3076659 |
| concepts[2].display_name | Tractography |
| concepts[3].id | https://openalex.org/C176217482 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5643181800842285 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q860554 |
| concepts[3].display_name | Metric (unit) |
| concepts[4].id | https://openalex.org/C106953101 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4854345917701721 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1814838 |
| concepts[4].display_name | Parallel transport |
| concepts[5].id | https://openalex.org/C60439489 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4837072491645813 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q634407 |
| concepts[5].display_name | Streamlines, streaklines, and pathlines |
| concepts[6].id | https://openalex.org/C149550507 |
| concepts[6].level | 3 |
| concepts[6].score | 0.478330135345459 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q899360 |
| concepts[6].display_name | Diffusion MRI |
| concepts[7].id | https://openalex.org/C154945302 |
| concepts[7].level | 1 |
| concepts[7].score | 0.47527876496315 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[7].display_name | Artificial intelligence |
| concepts[8].id | https://openalex.org/C89600930 |
| concepts[8].level | 2 |
| concepts[8].score | 0.469078004360199 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q1423946 |
| concepts[8].display_name | Segmentation |
| concepts[9].id | https://openalex.org/C2780297707 |
| concepts[9].level | 2 |
| concepts[9].score | 0.46084094047546387 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q4895393 |
| concepts[9].display_name | Landmark |
| concepts[10].id | https://openalex.org/C146710177 |
| concepts[10].level | 3 |
| concepts[10].score | 0.45442724227905273 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q1154996 |
| concepts[10].display_name | Fiber bundle |
| concepts[11].id | https://openalex.org/C2781192897 |
| concepts[11].level | 3 |
| concepts[11].score | 0.425055593252182 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q822050 |
| concepts[11].display_name | White matter |
| concepts[12].id | https://openalex.org/C204366326 |
| concepts[12].level | 2 |
| concepts[12].score | 0.4242340326309204 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q3027650 |
| concepts[12].display_name | Deformation (meteorology) |
| concepts[13].id | https://openalex.org/C2524010 |
| concepts[13].level | 1 |
| concepts[13].score | 0.3777168393135071 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[13].display_name | Geometry |
| concepts[14].id | https://openalex.org/C41008148 |
| concepts[14].level | 0 |
| concepts[14].score | 0.3759581744670868 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[14].display_name | Computer science |
| concepts[15].id | https://openalex.org/C519885992 |
| concepts[15].level | 2 |
| concepts[15].score | 0.3581838011741638 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q161 |
| concepts[15].display_name | Fiber |
| concepts[16].id | https://openalex.org/C105702510 |
| concepts[16].level | 1 |
| concepts[16].score | 0.35324758291244507 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q514 |
| concepts[16].display_name | Anatomy |
| concepts[17].id | https://openalex.org/C33923547 |
| concepts[17].level | 0 |
| concepts[17].score | 0.3431742787361145 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[17].display_name | Mathematics |
| concepts[18].id | https://openalex.org/C121332964 |
| concepts[18].level | 0 |
| concepts[18].score | 0.26822298765182495 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[18].display_name | Physics |
| concepts[19].id | https://openalex.org/C86803240 |
| concepts[19].level | 0 |
| concepts[19].score | 0.26187899708747864 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[19].display_name | Biology |
| concepts[20].id | https://openalex.org/C71924100 |
| concepts[20].level | 0 |
| concepts[20].score | 0.13790073990821838 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[20].display_name | Medicine |
| concepts[21].id | https://openalex.org/C143409427 |
| concepts[21].level | 2 |
| concepts[21].score | 0.103687584400177 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q161238 |
| concepts[21].display_name | Magnetic resonance imaging |
| concepts[22].id | https://openalex.org/C126838900 |
| concepts[22].level | 1 |
| concepts[22].score | 0.08485370874404907 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q77604 |
| concepts[22].display_name | Radiology |
| concepts[23].id | https://openalex.org/C192562407 |
| concepts[23].level | 0 |
| concepts[23].score | 0.07937043905258179 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[23].display_name | Materials science |
| concepts[24].id | https://openalex.org/C159985019 |
| concepts[24].level | 1 |
| concepts[24].score | 0.0 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q181790 |
| concepts[24].display_name | Composite material |
| concepts[25].id | https://openalex.org/C153294291 |
| concepts[25].level | 1 |
| concepts[25].score | 0.0 |
| concepts[25].wikidata | https://www.wikidata.org/wiki/Q25261 |
| concepts[25].display_name | Meteorology |
| concepts[26].id | https://openalex.org/C162324750 |
| concepts[26].level | 0 |
| concepts[26].score | 0.0 |
| concepts[26].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[26].display_name | Economics |
| concepts[27].id | https://openalex.org/C21547014 |
| concepts[27].level | 1 |
| concepts[27].score | 0.0 |
| concepts[27].wikidata | https://www.wikidata.org/wiki/Q1423657 |
| concepts[27].display_name | Operations management |
| concepts[28].id | https://openalex.org/C97355855 |
| concepts[28].level | 1 |
| concepts[28].score | 0.0 |
| concepts[28].wikidata | https://www.wikidata.org/wiki/Q11473 |
| concepts[28].display_name | Thermodynamics |
| keywords[0].id | https://openalex.org/keywords/fiber-tract |
| keywords[0].score | 0.7442804574966431 |
| keywords[0].display_name | Fiber tract |
| keywords[1].id | https://openalex.org/keywords/tangent |
| keywords[1].score | 0.6771615743637085 |
| keywords[1].display_name | Tangent |
| keywords[2].id | https://openalex.org/keywords/tractography |
| keywords[2].score | 0.6400036811828613 |
| keywords[2].display_name | Tractography |
| keywords[3].id | https://openalex.org/keywords/metric |
| keywords[3].score | 0.5643181800842285 |
| keywords[3].display_name | Metric (unit) |
| keywords[4].id | https://openalex.org/keywords/parallel-transport |
| keywords[4].score | 0.4854345917701721 |
| keywords[4].display_name | Parallel transport |
| keywords[5].id | https://openalex.org/keywords/streamlines-streaklines-and-pathlines |
| keywords[5].score | 0.4837072491645813 |
| keywords[5].display_name | Streamlines, streaklines, and pathlines |
| keywords[6].id | https://openalex.org/keywords/diffusion-mri |
| keywords[6].score | 0.478330135345459 |
| keywords[6].display_name | Diffusion MRI |
| keywords[7].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[7].score | 0.47527876496315 |
| keywords[7].display_name | Artificial intelligence |
| keywords[8].id | https://openalex.org/keywords/segmentation |
| keywords[8].score | 0.469078004360199 |
| keywords[8].display_name | Segmentation |
| keywords[9].id | https://openalex.org/keywords/landmark |
| keywords[9].score | 0.46084094047546387 |
| keywords[9].display_name | Landmark |
| keywords[10].id | https://openalex.org/keywords/fiber-bundle |
| keywords[10].score | 0.45442724227905273 |
| keywords[10].display_name | Fiber bundle |
| keywords[11].id | https://openalex.org/keywords/white-matter |
| keywords[11].score | 0.425055593252182 |
| keywords[11].display_name | White matter |
| keywords[12].id | https://openalex.org/keywords/deformation |
| keywords[12].score | 0.4242340326309204 |
| keywords[12].display_name | Deformation (meteorology) |
| keywords[13].id | https://openalex.org/keywords/geometry |
| keywords[13].score | 0.3777168393135071 |
| keywords[13].display_name | Geometry |
| keywords[14].id | https://openalex.org/keywords/computer-science |
| keywords[14].score | 0.3759581744670868 |
| keywords[14].display_name | Computer science |
| keywords[15].id | https://openalex.org/keywords/fiber |
| keywords[15].score | 0.3581838011741638 |
| keywords[15].display_name | Fiber |
| keywords[16].id | https://openalex.org/keywords/anatomy |
| keywords[16].score | 0.35324758291244507 |
| keywords[16].display_name | Anatomy |
| keywords[17].id | https://openalex.org/keywords/mathematics |
| keywords[17].score | 0.3431742787361145 |
| keywords[17].display_name | Mathematics |
| keywords[18].id | https://openalex.org/keywords/physics |
| keywords[18].score | 0.26822298765182495 |
| keywords[18].display_name | Physics |
| keywords[19].id | https://openalex.org/keywords/biology |
| keywords[19].score | 0.26187899708747864 |
| keywords[19].display_name | Biology |
| keywords[20].id | https://openalex.org/keywords/medicine |
| keywords[20].score | 0.13790073990821838 |
| keywords[20].display_name | Medicine |
| keywords[21].id | https://openalex.org/keywords/magnetic-resonance-imaging |
| keywords[21].score | 0.103687584400177 |
| keywords[21].display_name | Magnetic resonance imaging |
| keywords[22].id | https://openalex.org/keywords/radiology |
| keywords[22].score | 0.08485370874404907 |
| keywords[22].display_name | Radiology |
| keywords[23].id | https://openalex.org/keywords/materials-science |
| keywords[23].score | 0.07937043905258179 |
| keywords[23].display_name | Materials science |
| language | |
| locations[0].id | pmh:oai:arXiv.org:2108.03697 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2108.03697 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2108.03697 |
| indexed_in | arxiv |
| authorships[0].author.id | https://openalex.org/A5024674786 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Andrew Lizarraga |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Lizarraga, Andrew |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5100423797 |
| authorships[1].author.orcid | https://orcid.org/0009-0006-5423-4525 |
| authorships[1].author.display_name | David Lee |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Lee, David |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5034230412 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-6310-9415 |
| authorships[2].author.display_name | Antoni Kubicki |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Kubicki, Antoni |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5000858271 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-0622-9634 |
| authorships[3].author.display_name | Ashish Sahib |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Sahib, Ashish |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5087558885 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Elvis Nunez |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Nunez, Elvis |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5083948964 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-9396-7936 |
| authorships[5].author.display_name | Katherine L. Narr |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Narr, Katherine |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5115590666 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-7292-8022 |
| authorships[6].author.display_name | Shantanu H. Joshi |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Joshi, Shantanu H. |
| authorships[6].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2108.03697 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2022-07-25T00:00:00 |
| display_name | Alignment of Tractography Streamlines using Deformation Transfer via\n Parallel Transport |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11304 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9998000264167786 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2741 |
| primary_topic.subfield.display_name | Radiology, Nuclear Medicine and Imaging |
| primary_topic.display_name | Advanced Neuroimaging Techniques and Applications |
| related_works | https://openalex.org/W2094435366, https://openalex.org/W795339718, https://openalex.org/W135329292, https://openalex.org/W2032211030, https://openalex.org/W2313075602, https://openalex.org/W1988951906, https://openalex.org/W2914148974, https://openalex.org/W3190564354, https://openalex.org/W205576738, https://openalex.org/W2062477310 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | pmh:oai:arXiv.org:2108.03697 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2108.03697 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2108.03697 |
| primary_location.id | pmh:oai:arXiv.org:2108.03697 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2108.03697 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2108.03697 |
| publication_date | 2021-08-08 |
| publication_year | 2021 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 2, 50, 64, 92, 109 |
| abstract_inverted_index.43 | 112 |
| abstract_inverted_index.In | 87 |
| abstract_inverted_index.We | 0, 48, 102 |
| abstract_inverted_index.an | 73 |
| abstract_inverted_index.by | 72, 81 |
| abstract_inverted_index.is | 36 |
| abstract_inverted_index.of | 32, 106, 111 |
| abstract_inverted_index.on | 108 |
| abstract_inverted_index.to | 18, 58 |
| abstract_inverted_index.and | 97 |
| abstract_inverted_index.are | 70 |
| abstract_inverted_index.can | 90 |
| abstract_inverted_index.for | 5 |
| abstract_inverted_index.one | 16, 57, 89 |
| abstract_inverted_index.see | 19 |
| abstract_inverted_index.the | 30, 85, 104 |
| abstract_inverted_index.from | 84 |
| abstract_inverted_index.mean | 75 |
| abstract_inverted_index.that | 23 |
| abstract_inverted_index.adult | 114 |
| abstract_inverted_index.along | 76 |
| abstract_inverted_index.fiber | 9, 12, 68 |
| abstract_inverted_index.mean. | 86 |
| abstract_inverted_index.novel | 51 |
| abstract_inverted_index.often | 24 |
| abstract_inverted_index.this, | 67 |
| abstract_inverted_index.while | 61 |
| abstract_inverted_index.white | 7, 33 |
| abstract_inverted_index.across | 42 |
| abstract_inverted_index.direct | 40 |
| abstract_inverted_index.fields | 79 |
| abstract_inverted_index.highly | 37 |
| abstract_inverted_index.matter | 8, 34 |
| abstract_inverted_index.metric | 53 |
| abstract_inverted_index.tracts | 13, 35, 55, 60, 69, 96 |
| abstract_inverted_index.between | 14, 54, 95 |
| abstract_inverted_index.brains, | 15 |
| abstract_inverted_index.compare | 59 |
| abstract_inverted_index.expects | 17 |
| abstract_inverted_index.finding | 39 |
| abstract_inverted_index.healthy | 113 |
| abstract_inverted_index.overlap | 20 |
| abstract_inverted_index.present | 1, 49, 103 |
| abstract_inverted_index.provide | 25 |
| abstract_inverted_index.remains | 45 |
| abstract_inverted_index.results | 105 |
| abstract_inverted_index.tangent | 82, 100 |
| abstract_inverted_index.tracts. | 10 |
| abstract_inverted_index.vectors | 83 |
| abstract_inverted_index.However, | 29 |
| abstract_inverted_index.aligning | 6 |
| abstract_inverted_index.geometry | 31 |
| abstract_inverted_index.multiple | 43 |
| abstract_inverted_index.parallel | 93 |
| abstract_inverted_index.problem. | 47 |
| abstract_inverted_index.vectors. | 101 |
| abstract_inverted_index.determine | 91 |
| abstract_inverted_index.framework | 4 |
| abstract_inverted_index.geometric | 3 |
| abstract_inverted_index.intrinsic | 74 |
| abstract_inverted_index.obtaining | 63 |
| abstract_inverted_index.transport | 94 |
| abstract_inverted_index.with\nthe | 77 |
| abstract_inverted_index.meaningful | 26 |
| abstract_inverted_index.population | 110 |
| abstract_inverted_index.structures | 22 |
| abstract_inverted_index.comparisons | 27 |
| abstract_inverted_index.deformation | 52, 78 |
| abstract_inverted_index.individuals | 44 |
| abstract_inverted_index.represented | 71, 80 |
| abstract_inverted_index.subjects.\n | 115 |
| abstract_inverted_index.that\nallows | 56 |
| abstract_inverted_index.corresponding | 99 |
| abstract_inverted_index.registration. | 65 |
| abstract_inverted_index.To\naccomplish | 66 |
| abstract_inverted_index.a\nchallenging | 46 |
| abstract_inverted_index.of\nanatomical | 21 |
| abstract_inverted_index.simultaneously | 62 |
| abstract_inverted_index.then\nregister | 98 |
| abstract_inverted_index.this\nsetting, | 88 |
| abstract_inverted_index.By\nregistering | 11 |
| abstract_inverted_index.across\nsubjects. | 28 |
| abstract_inverted_index.bundle\nalignment | 107 |
| abstract_inverted_index.heterogeneous,\nand | 38 |
| abstract_inverted_index.tract-correspondence | 41 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.3246177 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |