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Dataset for: Quantification of vascular networks in photoacoustic mesoscopy


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Authors

Lefebvre, Thierry 
Sweeney, Paul 
Stolz, Bernadette 
Groehl, Janek 

Description

The zip files contain the following data:

In the InSilico folder,

  1. RawLnet: Raw binary mask of an examplar L-System
  2. OpticalSimLnet: Intermediate L-Net post forward optical simulation
  3. AcousticSimLnet: Reconstructed L-Net post acoustic simulation
  4. FinalDenoisedLnet: Final denoised L-Net used for analysis
  5. VesselnessFilteredLNet: (optional) Vesselness filtered final L-Net
  6. SegmentedLNet: Final segmented L-Net using the four proposed methods (auto-thresholding, auto-thresholding + vesselness filtering, random forest, random forest + vesselness filtering)

In the Phantom folder,

  1. RawPhantom: Raw reconstructed string image exported from the RSOM
  2. FinalDenoisedPhantom: Final denoised string image used for analysis
  3. VesselnessFilteredPhantom: (optional) Vesselness filtered string image
  4. SegmentedPhantom: Final segmented string image using the four proposed methods (auto-thresholding, auto-thresholding + vesselness filtering, random forest, random forest + vesselness filtering)

In the InVivo folder,

  1. RawRSOM: Raw reconstructed tumour image exported from the RSOM
  2. FinalDenoisedRSOM: Final denoised tumour image used for analysis
  3. VesselnessFilteredRSOM: (optional) Vesselness filtered tumour image
  4. SegmentedRSOM: Final segmented tumour image using the four proposed methods (auto-thresholding, auto-thresholding + vesselness filtering, random forest, random forest + vesselness filtering)

Version

Software / Usage instructions

The software associated with the deposited data is a series of custom codes that are hosted on publicly available repositories. Code to generate synthetic vascular trees (LNets) is available on GitHub (https://github.com/psweens/V-System). In silico photoacoustic simulations were performed using the SIMPA toolkit (https://github.com/CAMI-DKFZ/simpa). Both the trained 3D CNN to extract tumour ROIs from RSOM images (https://github.com/psweens/Predict-RSOM-ROI) and vascular TDA package are available on GitHub (https://github.com/psweens/Vascular-TDA).

Keywords

photoacoustic, vessel networks, topological data analysis, mesoscopy

Publisher

Sponsorship
Cancer Research UK (C14303/A17197)
Engineering and Physical Sciences Research Council (EP/N014588/1)
Cancer Research UK (C14303/A17197)
National Physical Laboratory (NPL) (unknown)
National Physical Laboratory (NPL) (unknown)
National Physical Laboratory (NPL) (unknown)
Cancer Research UK (C47594/A29448)
Relationships
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