Evidence map›Paper›PMID 39627257›Full record

ArticleScientific data2024

GeoCrack: A High-Resolution Dataset For Segmentation of Fracture Edges in Geological Outcrops.

Mohammed Yaqoob, Mohammed Ishaq, Mohammed Yusuf Ansari, Venkata Ram Sagar Konagandla, Tamim Al Tamimi, Stefano Tavani, Amerigo Corradetti, Thomas Daniel Seers

Abstract read
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 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

8 authors.

Mohammed Yaqoob *Texas A&M University, Electrical and Computer Engineering, Doha, Qatar. yansari@tamu.edu.ORCID http://orcid.org/0000-0002-6335-6923
Mohammed Ishaq *Texas A&M University, Electrical and Computer Engineering, Doha, Qatar.
Mohammed Yusuf Ansari *Texas A&M University, Electrical and Computer Engineering, Doha, Qatar.
Venkata Ram Sagar KonagandlaTexas A&M University, Petroleum Engineering, Doha, Qatar.
Tamim Al TamimiTexas A&M University, Electrical and Computer Engineering, Doha, Qatar.
Stefano TavaniDipartimento di Scienze della Terra, dell'Ambiente e delle Risorse, University of Naples, Naples, Italy.
Amerigo CorradettiDipartimento di Matematica, Informatica e Geoscienze, University of Trieste, Trieste, Italy.ORCID http://orcid.org/0000-0002-5174-0653
Thomas Daniel SeersTexas A&M University, Petroleum Engineering, Doha, Qatar.

Funding

Qatar National Research Fund (QNRF) Project: NPRP10-0104-170104-491140
6 · The paper itself

Abstract

GeoCrack is the first large-scale open source annotated dataset of fracture traces from geological outcrops, enabling deep learning-based fracture segmentation, setting a new standard for natural fracture characterization datasets. GeoCrack contains images from photogrammetric surveys of fractured rock exposures across 11 sites in Europe and the Middle East, capturing diverse lithologies and tectonic settings. Each image was cleaned, normalized, and manually segmented, followed by a recursive annotation vetting process to ensure the quality and accuracy of the digitized fracture edges. The processed images and corresponding binary masks were divided into 224 × 224 patches, yielding 12,158 pairs. GeoCrack captures representive real-world challenges in fracture edge annotation, such as contrast variations between fracture traces and the host medium due to geological and geomorphological factors like aperture dilation, host rock composition, outcrop weathering, and groundwater staining. Physical occlusions like shadows and vegetation are also considered to minimize false positives. GeoCrack was validated using a U-Net implementation for fracture segmentation, achieving satisfactory IoU of 85%. GeoCrack holds strong potential to advance deep fracture segmentation in geological applications, effectively tackling the diverse challenges of real-world fracture identification.

Identifiers

PMID39627257
PMCPMC11615390

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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.