@software{glenn_jocher_2021_4418161,
  author       = {Glenn Jocher and
                  Alex Stoken and
                  Jirka Borovec},
  title        = {{ultralytics/yolov5: v4.0}},
  month        = jan,
  year         = 2021,
  publisher    = {Zenodo},
  version      = {v4.0},
  doi          = {10.5281/zenodo.4418161},
  url          = {https://doi.org/10.5281/zenodo.4418161}
}

%  - nn.SiLU() activations, Weights \& Biases logging, PyTorch Hub integration

% NanoCode012 and
%   ChristopherSTAN and
%   Liu Changyu and
%   Laughing and
%   tkianai and
%   yxNONG and
%   Adam Hogan and
%   lorenzomammana and
%   AlexWang1900 and
%   Ayush Chaurasia and
%   Laurentiu Diaconu and
%   Marc and
%   wanghaoyang0106 and
%   ml5ah and
%   Doug and
%   Durgesh and
%   Francisco Ingham and
%   Frederik and
%   Guilhen and
%   Adrien Colmagro and
%   Hu Ye and
%   Jacobsolawetz and
%   Jake Poznanski and
%   Jiacong Fang and
%   Junghoon Kim and
%   Khiem Doan and
%   Lijun Yu 于力军

@inproceedings{lin2014microsoft,
  title={Microsoft coco: Common objects in context},
  author={Tsung-Yi and Maire, Michael and Belongie, Serge and Hays, James and Perona, Pietro and Ramanan, Deva and Doll{\'a}r, Piotr and Zitnick, C Lawrence},
  booktitle={European conference on computer vision},
  pages={740--755},
  year={2014},
  organization={Springer}
}

% Not added to diag.bib

@inproceedings{yoo2019pseudoedgenet,
  title={PseudoEdgeNet: nuclei segmentation only with point annotations},
  author={Yoo, Inwan and Yoo, Donggeun and Paeng, Kyunghyun},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={731--739},
  year={2019},
  organization={Springer}
}

@inproceedings{laradji2018blobs,
  title={Where are the blobs: Counting by localization with point supervision},
  author={Laradji, Issam H and Rostamzadeh, Negar and Pinheiro, Pedro O and Vazquez, David and Schmidt, Mark},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
  pages={547--562},
  year={2018}
}

@article {Alth19,
	author = {Althammer, Sonja and Tan, Tze Heng and Spitzm{\"u}ller, Andreas and Steele, Keith E.},
	title = {Automated image analysis of NSCLC biopsies to predict response to anti-PD-L1 therapy},
	volume = {7},
	number = {1},
	elocation-id = {121},
	year = {2019},
	doi = {10.1186/s40425-019-0589-x},
	publisher = {BMJ Specialist Journals},
	abstract = {Background Immune checkpoint therapies (ICTs) targeting the programmed cell death-1 (PD1)/programmed cell death ligand-1 (PD-L1) pathway have improved outcomes for patients with non-small cell lung cancer (NSCLC), particularly those with high PD-L1 expression. However, the predictive value of manual PD-L1 scoring is imperfect and alternative measures are needed. We report an automated image analysis solution to determine the predictive and prognostic values of the product of PD-L1+ cell and CD8+ tumor infiltrating lymphocyte (TIL) densities (CD8xPD-L1 signature) in baseline tumor biopsies.Methods Archival or fresh tumor biopsies were analyzed for PD-L1 and CD8 expression by immunohistochemistry. Samples were collected from 163 patients in Study 1108/NCT01693562, a Phase 1/2 trial to evaluate durvalumab across multiple tumor types, including NSCLC, and a separate cohort of 199 non-ICT- patients. Digital images were automatically scored for PD-L1+ and CD8+ cell densities using customized algorithms applied with Developer XD{\texttrademark} 2.7 software.Results For patients who received durvalumab, median overall survival (OS) was 21.0 months for CD8xPD-L1 signature-positive patients and 7.8 months for signature-negative patients (p~= 0.00002). The CD8xPD-L1 signature provided greater stratification of OS than high densities of CD8+ cells, high densities of PD-L1+ cells, or manually assessed tumor cell PD-L1 expression >=25\%. The CD8xPD-L1 signature did not stratify OS in non-ICT patients, although a high density of CD8+ cells was associated with higher median OS (high: 67 months; low: 39.5 months, p~= 0.0009) in this group.Conclusions An automated CD8xPD-L1 signature may help to identify NSCLC patients with improved response to durvalumab therapy. Our data also support the prognostic value of CD8+ TILS in NSCLC patients who do not receive ICT.Trial registration ClinicalTrials.gov identifier: NCT01693562.Study code: CD-ON-MEDI4736-1108.Interventional study (ongoing but not currently recruiting).Actual study start date: August 29, 2012.Primary completion date: June 23, 2017 (final data collection date for primary outcome measure).Abbreviations:ANOVAAnalysis of varianceCD8Cluster of differentiation 8CIConfidence intervalICTImmune checkpoint therapyIHCImmunohistochemistryNRNot reachedNSCLCNon-small cell lung cancerORRObjective response rateOSOverall survivalPD1Programmed cell death-1PD-L1Programmed cell death ligand-1PFSProgression-free survivalPPVPositive predictive valueRECISTResponse Evaluation Criteria in Solid TumorsTCTumor cellTILTumor infiltrating lymphocyteTMBTumor mutational burden},
	eprint = {https://jitc.bmj.com/content/7/1/121.full.pdf},
	journal = {Journal for ImmunoTherapy of Cancer}
}

% Rognoni, Lorenz and Wiestler, Tobias and Herz, Thomas and Widmaier, Moritz and Rebelatto, Marlon C. and Kaplon, Helene and Damotte, Diane and Alifano, Marco and Hammond, Scott A. and Dieu-Nosjean, Marie-Caroline and Ranade, Koustubh and Schmidt, Guenter and Higgs, Brandon W.
% URL = {https://jitc.bmj.com/content/7/1/121},