Package: resector
resectorImplementation of aTorchIOtransform
used to simulate a resection cavity from a T1-weighted brain MRI and a
correspondinggeodesic information flows (GIF) brain parcellation (version 3.0).The corresponding talk at MICCAI 2020 is available on YouTube:CreditIf you use this library for your research, please cite the following publications:Pérez-García, F., Dorent, R., Rizzi, M., Cardinale, F., Frazzini, V., Navarro, V., Essert, C., Ollivier, I., Vercauteren, T., Sparks, R., Duncan, J.S., Ourselin, S.:A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections. International Journal of Computer Assisted Radiology and Surgery  –IJCARS(Jun 2021)Pérez-García, F., Rodionov, R., Alim-Marvasti, A., Sparks, R., Duncan, J.S., Ourselin, S.:Simulation of Brain Resection for Cavity Segmentation Using Selfsupervised and Semi-supervised Learning. In: Medical Image Computing and Computer Assisted Intervention –MICCAI 2020. pp. 115–125. Lecture Notes in Computer Science, Springer International Publishing, Cham (2020)Bibtex:@inproceedings{perez-garcia_simulation_2020,address={Cham},series={Lecture {Notes} in {Computer} {Science}},title={Simulation of {Brain} {Resection} for {Cavity} {Segmentation} {Using} {Self}-supervised and {Semi}-supervised {Learning}},isbn={978-3-030-59716-0},doi={10.1007/978-3-030-59716-0\_12},language={en},booktitle={Medical {Image} {Computing} and {Computer} {Assisted} {Intervention} {\textendash} {MICCAI} 2020},publisher={Springer International Publishing},author={P{\'e}rez-Garc{\'i}a, Fernando and Rodionov, Roman and Alim-Marvasti, Ali and Sparks, Rachel and Duncan, John S. and Ourselin, S{\'e}bastien},year={2020},keywords={Segmentation, Self-supervised learning, Neurosurgery},pages={115--125},}@article{perez-garcia_self-supervised_2021,title={A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections},issn={1861-6429},url={https://doi.org/10.1007/s11548-021-02420-2},doi={10.1007/s11548-021-02420-2},language={en},urldate={2021-06-14},journal={International Journal of Computer Assisted Radiology and Surgery},author={P{\'e}rez-Garc{\'i}a, Fernando and Dorent, Reuben and Rizzi, Michele and Cardinale, Francesco and Frazzini, Valerio and Navarro, Vincent and Essert, Caroline and Ollivier, Ir{\`e}ne and Vercauteren, Tom and Sparks, Rachel and Duncan, John S. and Ourselin, S{\'e}bastien},month=jun,year={2021},file={Springer Full Text PDF:/Users/fernando/Zotero/storage/SM9WHUB7/P{\'e}rez-Garc{\'i}a et al. - 2021 - A self-supervised learning strategy for postoperat.pdf:application/pdf},}InstallationUsingcondais recommended:condacreate--nameresenvpython=3.8--yes&&condaactivateresenv
pipinstalllight-the-torch
lttinstalltorch
pipinstallgit+https://github.com/fepegar/resector
resect--helpUsageresectt1.nii.gzgif_parcellation.nii.gzt1_resected.nii.gzt1_resection_label.nii.gzTorchIO, which is installed withresector, can be used to download some sample images:T1=`python-c"import torchio as tio; print(tio.datasets.FPG().t1.path)"`GIF=`python-c"import torchio as tio; print(tio.datasets.FPG().seg.path)"`resect$T1$GIFt1_resected.nii.gzt1_resection_label.nii.gzRunresect --helpfor more options.FundingThis work was funded by theEngineering and Physical Sciences Research Council (EPSRC)and theWellcome Trust.It was additionally supported by theEPSRC-funded UCL Centre for Doctoral Training in Intelligent, Integrated Imaging in Healthcare (i4health)and theWellcome / EPSRC Centre for Interventional and Surgical Sciences (WEISS).