Home › Entities › academia › A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age

A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age

Research article (NeuroImage, 2015) · cited 33× · AI/ML
academia openalex:W254543832
Press Enter · cited answer in seconds

A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age

Summary

A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age is a scholarly article[1].

Key Facts

  • A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age's Applications to automated white matter/gray matter segmentation and tensor-based morphometry is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-reliable-spatially-normalized-template-of-the-human-spinal-cord-applications-to-automated-white-matter-gray-matter-seg
MLA “A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-reliable-spatially-normalized-template-of-the-human-spinal-cord-applications-to-automated-white-matter-gray-matter-seg.
BibTeX @misc{4ortxyz_a-reliable-spatially-normalized-template-of-the-human-spinal-cord-applications-to-automated-white-matter-gray-matter-seg_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age}}, year = {2026}, url = {https://4ort.xyz/entity/a-reliable-spatially-normalized-template-of-the-human-spinal-cord-applications-to-automated-white-matter-gray-matter-seg}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age — https://4ort.xyz/entity/a-reliable-spatially-normalized-template-of-the-human-spinal-cord-applications-to-automated-white-matter-gray-matter-seg (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/a-reliable-spatially-normalized-template-of-the-human-spinal-cord-applications-to-automated-white-matter-gray-matter-seg · Last refreshed: