Astley JR, Biancardi AM, Marshall H, Hughes PJC, Collier GJ, Hatton MQ, Wild JM, Tahir BA (2023) A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI. Med Phys 50(9):5657–5670. https://doi.org/10.1002/mp.16369

Article  PubMed  Google Scholar 

Astley JR, Wild JM, Tahir BA (2022) Deep learning in structural and functional lung image analysis. British J Radiol 95(1132):20201107

Article  Google Scholar 

Bajc M, Neilly JB, Miniati M, Schuemichen C, Meignan M, Jonson B (2009) EANM guidelines for ventilation/perfusion scintigraphy: Part 1. Pulmonary imaging with ventilation/perfusion single photon emission tomography. Eur J Nuclear Med Molecular Imag 36(8):1356–1370

Article  Google Scholar 

Castillo E, Castillo R, Vinogradskiy Y, Dougherty M, Solis D, Myziuk N, Thompson A, Guerra R, Nair G, Guerrero T (2019) Robust CT ventilation from the integral formulation of the Jacobian. Med Phys 46(5):2115–2125. https://doi.org/10.1002/mp.13453

Article  PubMed  Google Scholar 

Castillo E, Castillo R, Vinogradskiy Y, Guerrero T (2017) The numerical stability of transformation-based CT ventilation. Int J Comput Assist Radiol Surg 12(4):569–580

Article  PubMed  PubMed Central  Google Scholar 

Castillo E, Nair G, Turner-Lawrence D, Myziuk N, Emerson S, Al-Katib S, Westergaard S, Castillo R, Vinogradskiy Y, Quinn T, Guerrero T, Stevens C (2021) Quantifying pulmonary perfusion from noncontrast computed tomography. Med Phys 48(4):1804–1814. https://doi.org/10.1002/mp.14792

Article  PubMed  Google Scholar 

Castillo R, Castillo E, Guerra R, Johnson VE, McPhail T, Garg AK, Guerrero T (2009) A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets. Phys Med Biol 54(7):1849–1870

Article  PubMed  Google Scholar 

Cazoulat G, Balter JM, Matuszak MM, Jolly S, Owen D, Brock KK (2021) Mapping lung ventilation through stress maps derived from biomechanical models of the lung. Med Phys 48(2):715–723

Article  PubMed  Google Scholar 

Chartrand G, Cheng PM, Vorontsov E, Drozdzal M, Turcotte S, Pal CJ, Kadoury S, Tang A (2017) Deep learning: A primer for radiologists. RadioGraphics. 37(7):2113–2131

Article  PubMed  Google Scholar 

Dhawan RT, Gopalan D, Howard L, Vicente A, Park M, Manalan K, Wallner I, Marsden P, Dave S, Branley H, Russell G, Dharmarajah N, Kon OM (2021) Beyond the clot: perfusion imaging of the pulmonary vasculature after COVID-19. The Lancet Respir Med 9(1):107–116

Article  PubMed  Google Scholar 

Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, Dehghani M, Minderer M, Heigold G, Gelly S, Uszkoreit J, Houlsby N (2021) An image is worth 16x16 words: Transformers for image recognition at scale. arXiv:2010.11929 [cs].

Eichinger M, Puderbach M, Fink C, Gahr J, Ley S, Plathow C, Tuengerthal S, Zuna I, Müller F-M, Kauczor H-U (2006) Contrast-enhanced 3D MRI of lung perfusion in children with cystic fibrosis—initial results. Eur Radiol 16(10):2147–2152

Article  PubMed  Google Scholar 

Elojeimy S, Cruite I, Bowen S, Zeng J, Vesselle H (2016) Overview of the novel and improved pulmonary ventilation-perfusion imaging applications in the Era of SPECT/CT. Am J Roentgenol 207(6):1307–1315

Article  Google Scholar 

Eslick EM, Stevens MJ, Bailey DL (2019) SPECT V/Q in Lung Cancer Radiotherapy Planning. Semin Nucl Med 49(1):31–36

Article  PubMed  Google Scholar 

Faught AM, Miyasaka Y, Kadoya N, Castillo R, Castillo E, Vinogradskiy Y, Yamamoto T (2017) Evaluating the toxicity reduction with computed tomographic ventilation functional avoidance radiation therapy. Int J Radiation Oncol Biol Phys 99(2):325–333

Article  Google Scholar 

Hatamizadeh A, Tang Y, Nath V, Yang D, Myronenko A, Landman B, Roth HR, Xu D (2022) UNETR: Transformers for 3D medical image segmentation. In: 2022 IEEE/CVF winter conference on applications of computer vision (WACV), pp 1748–1758, Waikoloa, HI, USA, January 2022. IEEE.

Hoover DA, Capaldi DPI, Sheikh K, Palma DA, Rodrigues GB, Rashid Dar A, Yu E, Dingle B, Landis M, Kocha W, Sanatani M, Vincent M, Younus J, Kuruvilla S, Gaede S, Parraga G, Yaremko BP (2014) Functional lung avoidance for individualized radiotherapy (FLAIR): study protocol for a randomized, double-blind clinical trial. BMC Cancer 14(1):934

Article  PubMed  PubMed Central  Google Scholar 

Huang B, Law MW-M, Khong P-L (2009) Whole-body PET/CT scanning: estimation of radiation dose and cancer risk. Radiology 251(1):166–174

Article  PubMed  Google Scholar 

Huang G, Liu Z, van der Maaten L, Weinberger KQ (2017) Densely connected convolutional networks. 4700–4708.

Hugo GD, Weiss E, Sleeman WC, Balik S, Keall PJ, Lu J, Williamson JF (2016) Data from 4D lung imaging of NSCLC patients.

Kajikawa T, Kadoya N, Maehara Y, Miura H, Katsuta Y, Nagasawa S, Suzuki G, Yamazaki H, Tamaki N, Yamada K (2022) A deep learning method for translating 3DCT to SPECT ventilation imaging: First comparison with 81mKr-gas SPECT ventilation imaging. Med Phys 49(7):4353–4364. https://doi.org/10.1002/mp.15697

Article  PubMed  Google Scholar 

Karras T, Aittala M, Hellsten J, Laine S, Lehtinen J, Aila T (2020) Training generative adversarial networks with limited data. Adv Neural Inform Process Syst 33:12104–12114

Google Scholar 

Kaushik A, Jaimini A, Tripathi M, D’Souza M, Sharma R, Mondal A, Mishra AK, Dwarakanath BS (2015) Estimation of radiation dose to patients from 18FDG whole body PET/CT investigations using dynamic PET scan protocol. Indian J Med Res 142(6):721–731

Article  PubMed  PubMed Central  Google Scholar 

Koch G, Zemel R, Salakhutdinov R, et al. (2015) Siamese neural networks for one-shot image recognition. In: ICML deep learning workshop, volume 2, pages 1–30. Lille, Issue: 1.

Le Roux P-Y, Hicks RJ, Siva S, Hofman MS (2019) PET/CT lung ventilation and perfusion scanning using galligas and gallium-68-MAA. Semin Nucl Med 49(1):71–81

Article  PubMed  Google Scholar 

Liu Z, Miao J, Huang P, Wang W, Wang X, Zhai Y, Wang J, Zhou Z, Bi N, Tian Y, Dai J (2020) A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation. Med Phys 47(3):1249–1257. https://doi.org/10.1002/mp.14004

Article  PubMed  Google Scholar 

Mathew L, Wheatley A, Castillo R, Castillo E, Rodrigues G, Guerrero T, Parraga G (2012) Hyperpolarized 3He magnetic resonance imaging: Comparison with four-dimensional X-ray computed tomography imaging in lung cancer. Acad Radiol 19(12):1546–1553

Article  PubMed  Google Scholar 

Matuszak MM, Matrosic C, Jarema D, McShan DL, Stenmark MH, Owen D, Jolly S, Kong F-M, Ten Haken RK (2016) Priority-driven plan optimization in locally advanced lung patients based on perfusion SPECT imaging. Adv Radiation Oncol 1(4):281–289

Article  Google Scholar 

Mistry NN, Pollaro J, Song J, De Lin M, Johnson GA (2008) Pulmonary perfusion imaging in the rodent lung using dynamic contrast-enhanced MRI. Magn Resonance Med 59(2):289–297. https://doi.org/10.1002/mrm.21353

Article  Google Scholar 

Porter EM, Myziuk NK, Quinn TJ, Lozano D, Peterson AB, Quach DM, Siddiqui ZA, Guerrero TM (2021) Synthetic pulmonary perfusion images from 4DCT for functional avoidance using deep learning. Phys Med Biol 66(17):175005

Article  Google Scholar 

Ren G, Zhang J, Li T, Xiao H, Cheung LY, Ho WY, Qin J, Cai J (2021) Deep learning-based computed tomography perfusion mapping (DL-CTPM) for pulmonary CT-to-perfusion translation. Int J Radiation Oncol Biol Phys 110(5):1508–1518

Article  Google Scholar 

Simon BA (2000) Non-invasive imaging of regional lung function using X-Ray computed tomography. J Clin Monit Comput 16(5):433–442

Article  PubMed  Google Scholar 

Soffer S, Klang E, Shimon O, Barash Y, Cahan N, Greenspana H, Konen E (2021) Deep learning for pulmonary embolism detection on computed tomography pulmonary angiogram: a systematic review and meta-analysis. Scientif Rep 11(1):15814

Article  Google Scholar 

Tapson VF (2008) Acute pulmonary embolism. New England J Med 358(10):1037–1052. https://doi.org/10.1056/NEJMra072753

Article  Google Scholar 

Vandemeulebroucke J, Rit S, Kybic J, Clarysse P, Sarrut D (2011) Spatiotemporal motion estimation for respiratory-correlated imaging of the lungs. Med Phys 38(1):166–178

Article  PubMed  Google Scholar 

Vinogradskiy Y, Castillo R, Castillo E, Schubert L, Jones BL, Faught A, Gaspar LE, Kwak J, Bowles DW, Waxweiler T, Dougherty JM, Gao D, Stevens C, Miften M, Kavanagh B, Grills I, Rusthoven CG, Guerrero T (2022) Results of a multi-institutional phase 2 clinical trial for 4DCT-ventilation functional avoidance thoracic radiation therapy. Int J Radiat Oncol Biol Phys. 112(4):986–995

Article  PubMed  Google Scholar 

Wood KE (2002) Major pulmonary embolism: review of a pathophysiologic approach to the golden hour of hemodynamically significant pulmonary embolism. Chest 121(3):877–905

Article  PubMed  Google Scholar 

Yamamoto T, Kabus S, Klinder T, von Berg J, Lorenz C, Loo BW Jr, Keall PJ (2011) Four-dimensional computed tomography pulmonary ventilation images vary with deformable image registration algorithms and metrics. Med Phys. 38(3):1348–1358. https://doi.org/10.1118/1.3547719

Article  PubMed  Google Scholar 

Zhang H, Goodfellow I, Metaxas D, Odena A (2019) Self-attention generative adversarial networks. In: Chaudhuri K, Salakhutdinov R,(Eds), Proceedings of the 36th international conference on machine learning, vol. 97 of proceedings of machine learning research, pp 7354–7363. PMLR.