TY - JOUR AU - Kies, M. S. AU - Bennett, C. L. AU - Vokes, E. E. PY - 2001 DA - 2001// TI - Locally advanced head and neck cancer JO - Curr Treat Options in Oncol VL - 2 UR - https://doi.org/10.1007/s11864-001-0012-x DO - 10.1007/s11864-001-0012-x ID - Kies2001 ER - TY - JOUR AU - Al-Sarraf, M. PY - 2002 DA - 2002// TI - Treatment of locally advanced head and neck Cancer: historical and critical review JO - Cancer Control VL - 9 UR - https://doi.org/10.1177/107327480200900504 DO - 10.1177/107327480200900504 ID - Al-Sarraf2002 ER - TY - JOUR AU - Emami, B. AU - Lyman, J. AU - Brown, A. AU - Cola, L. AU - Goitein, M. AU - Munzenrider, J. E. AU - Shank, B. AU - Solin, L. J. AU - Wesson, M. PY - 1991 DA - 1991// TI - Tolerance of normal tissue to therapeutic irradiation JO - Int J Radiat Oncol VL - 21 UR - https://doi.org/10.1016/0360-3016(91)90171-Y DO - 10.1016/0360-3016(91)90171-Y ID - Emami1991 ER - TY - STD TI - Thorwarth D. Biologically adapted radiation therapy. Z Für Med Phys. 2017; https://doi.org/10.1016/j.zemedi.2017.08.001. ID - ref4 ER - TY - STD TI - A.M. Owrangi, P.B. Greer, C.K. Glide-Hurst, MRI-only treatment planning: benefits and challenges. Phys Med Biol. 63 (2018) 05TR01. https://doi.org/10.1088/1361-6560/aaaca4. ID - ref5 ER - TY - JOUR AU - Thorwarth, D. PY - 2019 DA - 2019// TI - MRgRT: Magnetresonanz-geführte Strahlentherapie JO - Z Für Med Phys. VL - 29 UR - https://doi.org/10.1016/j.zemedi.2018.10.006 DO - 10.1016/j.zemedi.2018.10.006 ID - Thorwarth2019 ER - TY - JOUR AU - Harari, P. M. AU - Song, S. AU - Tomé, W. A. PY - 2010 DA - 2010// TI - Emphasizing conformal avoidance versus target definition for IMRT planning in head-and-neck Cancer JO - Int J Radiat Oncol. VL - 77 UR - https://doi.org/10.1016/j.ijrobp.2009.09.062 DO - 10.1016/j.ijrobp.2009.09.062 ID - Harari2010 ER - TY - JOUR AU - Guezennec, C. AU - Bourhis, D. AU - Orlhac, F. AU - Robin, P. AU - Corre, J. -. B. AU - Delcroix, O. AU - Gobel, Y. AU - Schick, U. AU - Salaün, P. -. Y. AU - Abgral, R. PY - 2019 DA - 2019// TI - Inter-observer and segmentation method variability of textural analysis in pre-therapeutic FDG PET/CT in head and neck cancer JO - PLoS One VL - 14 UR - https://doi.org/10.1371/journal.pone.0214299 DO - 10.1371/journal.pone.0214299 ID - Guezennec2019 ER - TY - STD TI - Menze, B.H, Jakab A, Bauer S, Kalpathy-Cramer J, Farahani K, Kirby J, Burren Y, Porz N, Slotboom J, Wiest R, Lanczi L, Gerstner E, Weber, M.A, Arbel T, Avants, B.B, Ayache N, Buendia P, Collins, D.L, Cordier N, Corso, J.J, Criminisi A, Das T, Delingette H, Demiralp Ç, Durst, C.R, Dojat M, Doyle S, Festa J, Forbes F, Geremia E, Glocker B, Golland P, Guo X, Hamamci A, Iftekharuddin, K.M, Jena R, John, N. M, Konukoglu E, Lashkari D, Mariz, J.A, Meier R, Pereira S, Precup D, Price, S.J, Raviv, T.R, Reza, S.M.S, Ryan M, Sarikaya D, Schwartz L, Shin, H.C, Shotton J, Silva, C.A, Sousa N, Subbanna, N.K, Szekely G, Taylor, T.J, Thomas, O.M, Tustison, N.J, Unal G, Vasseur F, Wintermark M, Ye, D.H, Zhao L, Zhao B, Zikic D, Prastawa M, Reyes M, Leemput, K. V. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Trans Med Imag. 34 (2015) 1993–2024. https://doi.org/10.1109/TMI.2014.2377694. ID - ref9 ER - TY - JOUR AU - Litjens, G. AU - Kooi, T. AU - Bejnordi, B. E. AU - Setio, A. A. A. AU - Ciompi, F. AU - Ghafoorian, M. AU - Laak, J. A. W. M. AU - Ginneken, B. AU - Sánchez, C. I. PY - 2017 DA - 2017// TI - A survey on deep learning in medical image analysis JO - Med Image Anal VL - 42 UR - https://doi.org/10.1016/j.media.2017.07.005 DO - 10.1016/j.media.2017.07.005 ID - Litjens2017 ER - TY - JOUR AU - Maier, A. AU - Syben, C. AU - Lasser, T. AU - Riess, C. PY - 2019 DA - 2019// TI - A gentle introduction to deep learning in medical image processing JO - Z. Für Med. Phys. VL - 29 UR - https://doi.org/10.1016/j.zemedi.2018.12.003 DO - 10.1016/j.zemedi.2018.12.003 ID - Maier2019 ER - TY - JOUR AU - Lundervold, A. S. AU - Lundervold, A. PY - 2019 DA - 2019// TI - An overview of deep learning in medical imaging focusing on MRI JO - Z Für Med Phys VL - 29 UR - https://doi.org/10.1016/j.zemedi.2018.11.002 DO - 10.1016/j.zemedi.2018.11.002 ID - Lundervold2019 ER - TY - STD TI - Wee L, Dekker A. Data from head-neck-Radiomics-HN1 [data set]. Cancer Imag Arch. 2019; https://doi.org/10.7937/tcia.2019.8kap372n. ID - ref13 ER - TY - STD TI - M. Banko, E. Brill. Scaling to very very large corpora for natural language disambiguation, in: Proc. 39th Annu. Meet. Assoc. Comput. Linguist. Association for Computational Linguistics, Toulouse, France, 2001: pp. 26–33. https://doi.org/10.3115/1073012.1073017. ID - ref14 ER - TY - JOUR AU - Tofts, P. S. AU - Brix, G. AU - Buckley, D. L. AU - Evelhoch, J. L. AU - Henderson, E. AU - Knopp, M. V. AU - Larsson, H. B. W. AU - Lee, T. -. Y. AU - Mayr, N. A. AU - Parker, G. J. M. AU - Port, R. E. AU - Taylor, J. AU - Weisskoff, R. M. PY - 2018 DA - 2018// TI - Estimating kinetic parameters from dynamic contrast-enhanced t1-weighted MRI of a diffusable tracer: standardized quantities and symbols JO - J Magn Reson Imaging VL - 10 UR - https://doi.org/3.0.CO;2-S DO - 3.0.CO;2-S ID - Tofts2018 ER - TY - JOUR AU - Oudeman, J. AU - Coolen, B. F. AU - Mazzoli, V. AU - Maas, M. AU - Verhamme, C. AU - Brink, W. M. AU - Webb, A. G. AU - Strijkers, G. J. AU - Nederveen, A. J. PY - 2016 DA - 2016// TI - Diffusion-prepared neurography of the brachial plexus with a large field-of-view at 3T JO - J Magn Reson Imaging VL - 43 UR - https://doi.org/10.1002/jmri.25025 DO - 10.1002/jmri.25025 ID - Oudeman2016 ER - TY - JOUR AU - Jacobsen, N. AU - Deistung, A. AU - Timmann, D. AU - Goericke, S. L. AU - Reichenbach, J. R. AU - Güllmar, D. PY - 2019 DA - 2019// TI - Analysis of intensity normalization for optimal segmentation performance of a fully convolutional neural network JO - Z. Für Med. Phys. VL - 29 UR - https://doi.org/10.1016/j.zemedi.2018.11.004 DO - 10.1016/j.zemedi.2018.11.004 ID - Jacobsen2019 ER - TY - JOUR AU - Kamnitsas, K. AU - Ledig, C. AU - Newcombe, V. F. J. AU - Simpson, J. P. AU - Kane, A. D. AU - Menon, D. K. AU - Rueckert, D. AU - Glocker, B. PY - 2017 DA - 2017// TI - Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation JO - Med Image Anal VL - 36 UR - https://doi.org/10.1016/j.media.2016.10.004 DO - 10.1016/j.media.2016.10.004 ID - Kamnitsas2017 ER - TY - STD TI - Krähenbühl P, Koltun V. Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials. arXiv:12105644 [cs] [Internet]. 2012. Available from: http://arxiv.org/abs/1210.5644. [cited 2018 Jul 3]. UR - http://arxiv.org/abs/1210.5644 ID - ref19 ER - TY - JOUR AU - Fütterer, J. J. AU - Briganti, A. AU - Visschere, P. AU - Emberton, M. AU - Giannarini, G. AU - Kirkham, A. AU - Taneja, S. S. AU - Thoeny, H. AU - Villeirs, G. AU - Villers, A. PY - 2015 DA - 2015// TI - Can clinically significant prostate Cancer be detected with multiparametric magnetic resonance imaging? A systematic review of the literature JO - Eur Urol VL - 68 UR - https://doi.org/10.1016/j.eururo.2015.01.013 DO - 10.1016/j.eururo.2015.01.013 ID - Fütterer2015 ER - TY - JOUR AU - Steiger, P. AU - Thoeny, H. C. PY - 2016 DA - 2016// TI - Prostate MRI based on PI-RADS version 2: how we review and report JO - Cancer Imaging VL - 16 UR - https://doi.org/10.1186/s40644-016-0068-2 DO - 10.1186/s40644-016-0068-2 ID - Steiger2016 ER - TY - JOUR AU - Kuroki, Y. AU - Nasu, K. PY - 2008 DA - 2008// TI - Advances in breast MRI: diffusion-weighted imaging of the breast JO - Breast Cancer VL - 15 UR - https://doi.org/10.1007/s12282-008-0050-3 DO - 10.1007/s12282-008-0050-3 ID - Kuroki2008 ER - TY - JOUR AU - Bielak, L. AU - Wiedenmann, N. AU - Nicolay, N. H. AU - Lottner, T. AU - Fischer, J. AU - Bunea, H. AU - Grosu, A. -. L. AU - Bock, M. PY - 2019 DA - 2019// TI - Automatic tumor segmentation with a convolutional neural network in multiparametric MRI: influence of distortion correction JO - Tomogr J Imaging Res VL - 5 ID - Bielak2019 ER - TY - JOUR AU - Yan, D. AU - Ziaja, E. AU - Jaffray, D. AU - Wong, J. AU - Brabbins, D. AU - Vicini, F. AU - Martinez, A. PY - 1998 DA - 1998// TI - The use of adaptive radiation therapy to reduce setup error: a prospective clinical study JO - Int J Radiat Oncol VL - 41 UR - https://doi.org/10.1016/S0360-3016(97)00567-1 DO - 10.1016/S0360-3016(97)00567-1 ID - Yan1998 ER - TY - STD TI - P. Simard, B. Victorri, Y. Lecun, J.S. Denker, Tangent prop: A formalism for specifying selected invariances in adaptive networks, Adv. Neural Inf. Process. Syst. NIPS 1991 Denver CO. (1992). ID - ref25 ER - TY - STD TI - L. Perez, J. Wang, The effectiveness of data augmentation in image classification using deep learning, ArXiv171204621 Cs. (2017). ID - ref26 ER - TY - JOUR AU - Akkus, Z. AU - Galimzianova, A. AU - Hoogi, A. AU - Rubin, D. L. AU - Erickson, B. J. PY - 2017 DA - 2017// TI - Deep learning for brain MRI segmentation: state of the art and future directions JO - J Digit Imaging VL - 30 UR - https://doi.org/10.1007/s10278-017-9983-4 DO - 10.1007/s10278-017-9983-4 ID - Akkus2017 ER - TY - JOUR AU - Sharif, M. I. AU - Li, J. P. AU - Khan, M. A. AU - Saleem, M. A. PY - 2020 DA - 2020// TI - Active deep neural network features selection for segmentation and recognition of brain tumors using MRI images JO - Pattern Recogn Lett VL - 129 UR - https://doi.org/10.1016/j.patrec.2019.11.019 DO - 10.1016/j.patrec.2019.11.019 ID - Sharif2020 ER - TY - JOUR AU - Men, K. AU - Dai, J. AU - Li, Y. PY - 2017 DA - 2017// TI - Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks JO - Med Phys VL - 44 UR - https://doi.org/10.1002/mp.12602 DO - 10.1002/mp.12602 ID - Men2017 ER - TY - JOUR AU - Veen, J. AU - Willems, S. AU - Deschuymer, S. AU - Robben, D. AU - Crijns, W. AU - Maes, F. AU - Nuyts, S. PY - 2019 DA - 2019// TI - Benefits of deep learning for delineation of organs at risk in head and neck cancer JO - Radiother Oncol VL - 138 UR - https://doi.org/10.1016/j.radonc.2019.05.010 DO - 10.1016/j.radonc.2019.05.010 ID - Veen2019 ER - TY - STD TI - Y.M. Moe, A.R. Groendahl, M. Mulstad, O. Tomic, U. Indahl, E. Dale, E. Malinen, C.M. Futsaether, Deep learning for automatic tumour segmentation in PET/CT images of patients with head and neck cancers, ArXiv190800841 Eess. (2019). ID - ref31 ER - TY - STD TI - N. Wiedenmann, H. Bunea, H.C. Rischke, A. Bunea, L. Majerus, L. Bielak, A. Protopopov, U. Ludwig, M. Büchert, C. Stoykow, N.H. Nicolay, W.A. Weber, M. Mix, P.T. Meyer, J. Hennig, M. Bock, A.L. Grosu, Effect of radiochemotherapy on T2* MRI in HNSCC and its relation to FMISO PET derived hypoxia and FDG PET, Radiat. Oncol. Lond. Engl. 13 (2018). https://doi.org/10.1186/s13014-018-1103-1. ID - ref32 ER - TY - JOUR AU - Zhou, H. AU - Chiguru, S. AU - Hallac, R. R. AU - Yang, D. AU - Hao, G. AU - Peschke, P. AU - Mason, R. P. PY - 2019 DA - 2019// TI - Examining correlations of oxygen sensitive MRI (BOLD/TOLD) with [18F]FMISO PET in rat prostate tumors JO - Am J Nucl Med Mol Imaging VL - 9 ID - Zhou2019 ER - TY - JOUR AU - Stieb, S. AU - Eleftheriou, A. AU - Warnock, G. AU - Guckenberger, M. AU - Riesterer, O. PY - 2018 DA - 2018// TI - Longitudinal PET imaging of tumor hypoxia during the course of radiotherapy JO - Eur J Nucl Med Mol Imaging VL - 45 UR - https://doi.org/10.1007/s00259-018-4116-y DO - 10.1007/s00259-018-4116-y ID - Stieb2018 ER -