Evidence map›Paper›PMID 39379407›Full record

ArticleScientific data2024

ProstateZones - Segmentations of the prostatic zones and urethra for the PROSTATEx dataset.

William Holmlund, Attila Simkó, Karin Söderkvist, Péter Palásti, Szilvia Tótin, Kamilla Kalmár, Zsófia Domoki, Zsuzsanna Fejes, Zsigmond Tamás Kincses, Patrik Brynolfsson and 1 more

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In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

11 authors.

William HolmlundUmeå University, Department of Diagnostics and Intervention, Umeå, Sweden. william.holmlund@umu.se.ORCID 0009-0001-0988-0134
Attila SimkóUmeå University, Department of Diagnostics and Intervention, Umeå, Sweden.
Karin SöderkvistUmeå University, Department of Diagnostics and Intervention, Umeå, Sweden.
Péter PalástiUniversity of Szeged, Albert Szent-Györgyi Medical School, Department of Radiology, Szeged, Hungary.ORCID 0000-0003-4197-1623
Szilvia TótinUniversity of Szeged, Albert Szent-Györgyi Medical School, Department of Radiology, Szeged, Hungary.
Kamilla KalmárUniversity of Szeged, Albert Szent-Györgyi Medical School, Department of Radiology, Szeged, Hungary.
Zsófia DomokiUniversity of Szeged, Albert Szent-Györgyi Medical School, Department of Radiology, Szeged, Hungary.
Zsuzsanna FejesUniversity of Szeged, Albert Szent-Györgyi Medical School, Department of Radiology, Szeged, Hungary.
Zsigmond Tamás KincsesUniversity of Szeged, Albert Szent-Györgyi Medical School, Department of Radiology, Szeged, Hungary.
Patrik BrynolfssonUmeå University, Department of Diagnostics and Intervention, Umeå, Sweden.
Tufve NyholmUmeå University, Department of Diagnostics and Intervention, Umeå, Sweden. tufve.nyholm@umu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Manual segmentations are considered the gold standard for ground truth in machine learning applications. Such tasks are tedious and time-consuming, albeit necessary to train reliable models. In this work, we present a dataset with expert segmentations of the prostatic zones and urethra for 200 randomly selected patients from the PROSTATEx dataset. Notably, independent duplicate segmentations were performed for 40 patients, providing inter-reader variability data. This results in a total of 240 segmentations. This dataset can be used to train machine learning models or serve as an external test set for evaluating models trained on private data, thereby addressing a current gap in the field. The delineated structures and terminology adhere to the latest Prostate Imaging Reporting and Data Systems v2.1 guidelines, ensuring consistency.

Indexed as

Machine LearningProstateUrethraHumansMale

Identifiers

PMID39379407
PMCPMC11461788

What OpenQuestion holds

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LicenceCC BY
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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.