Automatic Gauze Tracking in Laparoscopic Surgery using Image Texture Analysis
Description of this data
This dataset contain the code, training, test images and the results of the analysed algorithms: LBP|VAR, CLBP and the convolutional neuronal network ResNet50.
In results/TruePosit_FalsePosit_FalseNeg appears in GREEN the blocks correctly classified as gauze (true positives), in RED the blocks wronly classified as gauze (false positives) and in YELLOW the blocks where the gauze has not been detected (false negatives).
results/blockValues contains the test images with the percentage of probability overprinted that the block is gauze, according to the neuronal network.
Experiment data files
Steps to reproduce
LBP|VAR contains the code of the
CNN contains the results and code for training and test the neural network. code/red_gasas.pt contains the neural network
Cite this dataset
de la Fuente, Eusebio (2019), “Automatic Gauze Tracking in Laparoscopic Surgery using Image Texture Analysis”, Mendeley Data, v3 http://dx.doi.org/10.17632/yh2yxwbc9m.3
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The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.