Evidence map›Paper›PMID 36759653›Full record

ArticleScientific reports2023

Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system.

Emmanuelle Renauld, Antoine Théberge, Laurent Petit, Jean-Christophe Houde, Maxime Descoteaux

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% of its field
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. LEARNING SPATIALLY-CONTINUOUS FIBER ORIENTATION FUNCTIONS.Proceedings. IEEE International Symposium on Biomedical Imaging · 2024
    Article
  7. 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

5 authors at 2 institutions in 2 countries.

Emmanuelle RenauldSherbrooke Connectivity Imaging Laboratory (SCIL), Computer Sciences Department, Université de Sherbrooke, Sherbrooke, Canada. emmanuelle.renauld@usherbrooke.ca.
Antoine ThébergeSherbrooke Connectivity Imaging Laboratory (SCIL), Computer Sciences Department, Université de Sherbrooke, Sherbrooke, Canada.
Laurent PetitUniversité de Bordeaux, CNRS, CEA, IMN, GIN, UMR 5293, 33000, Bordeaux, France.
Jean-Christophe HoudeImeka Solutions Inc, Sherbrooke, QC, Canada.
Maxime DescoteauxSherbrooke Connectivity Imaging Laboratory (SCIL), Computer Sciences Department, Université de Sherbrooke, Sherbrooke, Canada.
Université de Sherbrooke · CACentre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since 2015, research groups have sought to produce the ne plus ultra of tractography algorithms using the ISMRM 2015 Tractography Challenge as evaluation. In particular, since 2017, machine learning has made its entrance into the tractography world. The ISMRM 2015 Tractography Challenge is the most used phantom during tractography validation, although it contains limitations. Here, we offer a new scoring system for this phantom, where segmentation of the bundles is now based on manually defined regions of interest rather than on bundle recognition. Bundles are now more reliably segmented, offering more representative metrics for future users. New code is available online. Scores of the initial 96 submissions to the challenge are updated. Overall, conclusions from the 2015 challenge are confirmed with the new scoring, but individual tractogram scores have changed, and the data is much improved at the bundle- and streamline-level. This work also led to the production of a ground truth tractogram with less broken or looping streamlines and of an example of processed data, all available on the Tractometer website. This enhanced scoring system and new data should continue helping researchers develop and evaluate the next generation of tractography techniques.

Indexed as

White MatterAlgorithmsBrainDiffusion Tensor ImagingImage Processing, Computer-AssistedMachine Learning

Identifiers

PMID36759653
PMCPMC9911766
OpenAlexW4319733470

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.