Publication: Detecting micro fractures with X-ray computed tomography

This dataverse includes the underlying data of the publication: Lee, D., Karadimitriou, N., Ruf, M., & Steeb, H. (2022). Detecting micro fractures: A comprehensive comparison of conventional and machine-learning based segmentation methods. Solid Earth (EGU). Submitted.

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1 to 10 of 13 Results

Chan_vese.m Jul 7, 2021 - Fracture network segmentation Plain Text - 5.3 KB - MD5: 42ba2403995ffbc255edfddfb575efa6 This file contains the workflow of Chan-Vese method
classifier.model Jul 7, 2021 - Fracture network segmentation Unknown - 1.9 GB - MD5: 9c0aaff5be02d37f4dd76756a142da01 This is the trained model with the Random forest method. This file could be loaded in the open source program ImageJ with TrainableWeka library. The predictions can be generated with processing.bsh code.
Frac_Unet_postprocess.py Jul 7, 2021 - Fracture network segmentation Plain Text - 3.0 KB - MD5: 8af741da7af5db62a1855a4c4eed56d0 With the code, the predictions of trained model for given input files can be generated and saved.
Frac_Unet_preprocess.py Jul 7, 2021 - Fracture network segmentation Plain Text - 2.2 KB - MD5: a269c380d683920ac900d3539a4fdc6a Preparation of training data can be done with the code
Frac_Unet_training.py Jul 7, 2021 - Fracture network segmentation Plain Text - 5.6 KB - MD5: 0d2949b2c023b9f5b67ccefb8487d803 With the pre-processed training data, the code performs training of U-net model and saves a trained model after training.
img_seg.py Jul 7, 2021 - Fracture network segmentation Plain Text - 15.4 KB - MD5: 9a20bdaef7a1f87ecfdd053873a642bf This file contains the load/save functions and core functions of the Sato and the Local threshold methods.
Local_threshold.py Jul 7, 2021 - Fracture network segmentation Plain Text - 1.5 KB - MD5: 68ae24ecafdaa06a04bf09504eb44fd2 This file contains the workflow of the local threshold method
post_random_forest.py Jul 7, 2021 - Fracture network segmentation Plain Text - 1.5 KB - MD5: 2c64aaca9f227470a4c9602988e8f9e8 The predictions of the Random forest method can be merged into the original size of image with the code.
processing.bsh Jul 7, 2021 - Fracture network segmentation Unknown - 2.0 KB - MD5: 4e3d9a1297a097e73d8e5433ca5449e3 Prediction generator of the random forest method. The input file path, save path and trained model have to be chosen.
readme.txt Jul 7, 2021 - Fracture network segmentation Plain Text - 2.6 KB - MD5: 1d388e58b5fd9037ef315ff386a6da77 This file contains instruction of how to operate the codes.

Chan_vese.m