Evidence map›Paper›PMID 33135015›Full record

ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2020

TRAKO: Efficient Transmission of Tractography Data for Visualization.

Daniel Haehn, Loraine Franke, Fan Zhang, Suheyla Cetin-Karayumak, Steve Pieper, Lauren J O'Donnell, Yogesh Rathi

Abstract read
In one paragraph

Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Daniel HaehnUniversity of Massachusetts Boston.ORCID 0000-0001-9144-3461
Loraine FrankeUniversity of Massachusetts Boston.ORCID 0000-0001-8560-2729
Fan ZhangHarvard Medical School.ORCID 0000-0002-5032-6039
Suheyla Cetin-KarayumakHarvard Medical School.ORCID 0000-0002-3315-5821
Steve PieperIsomics, Inc.ORCID 0000-0003-4193-9578
Lauren J O'DonnellHarvard Medical School.ORCID 0000-0003-0197-7801
Yogesh RathiHarvard Medical School.ORCID 0000-0002-9946-2314

Funding

Training and DisseminationP41EB015902 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI KIKINIS, RON, WESTIN, CARL-FREDRIK · 2012 to 2022
$20.9M
Harmonizing multi-site diffusion MRI acquisitions for neuroscientific analysis across ages and brain disordersR01MH119222 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI O'DONNELL, LAUREN JEAN, RATHI, YOGESH · 2019 to 2023
$4.0M
NIBIB NIH HHS P41 EB015902NIMH NIH HHS R01 MH119222
6 · The paper itself

Abstract

Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow for efficient storage, transfer, and visualization. We present TRAKO, a new data format based on the Graphics Layer Transmission Format (glTF) that enables immediate graphical and hardware-accelerated processing. We integrate a state-of-the-art compression technique for vertices, streamlines, and attached scalar and property data. We then compare TRAKO to existing tractography storage methods and provide a detailed evaluation on eight datasets. TRAKO can achieve data reductions of over 28x without loss of statistical significance when used to replicate analysis from previously published studies.

Indexed as

compressiondiffusion imagingtractography

Identifiers

PMID33135015
PMCPMC7597368

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.