3D Slicer as an image computing platform for the Quantitative Imaging Network

Jemal, 2011, Global cancer statistics, CA Cancer J Clin, 61, 69, 10.3322/caac.20107

Park, 2004, Rationale for biomarkers and surrogate end points in mechanism-driven oncology drug development, Clin Cancer Res, 10, 3885, 10.1158/1078-0432.CCR-03-0785

Jeraj, 2010, Imaging for assessment of radiation-induced normal tissue effects, Int J Radiat Oncol Biol Phys, 76, S140, 10.1016/j.ijrobp.2009.08.077

Eisenhauer E, Therasse P, Bogaerts J, Schwartz L, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). European journal of cancer (Oxford, England: 1990). 2009 January;45(2):228-247.

Jaffe, 2010, Quantitative imaging in oncology patients: part 1, radiology practice patterns at major U.S. cancer centers, AJR Am J Roentgenol, 195, 101, 10.2214/AJR.09.2850

Clarke, 2009, Quantitative imaging for evaluation of response to cancer therapy, Transl Oncol, 2, 195, 10.1593/tlo.09217

Gering DT. A System for Surgical Planning and Guidance using Image Fusion and Interventional MR. 1999:106.

Grimson, 1998, Vol. 1496, 63

Gering, 2001, An integrated visualization system for surgical planning and guidance using image fusion and an open MR, J Magn Reson Imaging, 13, 967, 10.1002/jmri.1139

Tempany, 2008, MR-guided prostate interventions, J Magn Reson Imaging, 27, 356, 10.1002/jmri.21259

Golby, 2011, Interactive diffusion tensor tractography visualization for neurosurgical planning, Neurosurgery, 68, 496, 10.1227/NEU.0b013e3182061ebb

Caskey, 2011, An open environment CT–US fusion for tissue segmentation during interventional guidance, PLoS One, 6, e27372, 10.1371/journal.pone.0027372

Frisardi, 2011, Integration of 3D anatomical data obtained by CT imaging and 3D optical scanning for computer aided implant surgery, BMC Med Imaging, 11, 5, 10.1186/1471-2342-11-5

Uneri, 2011, TREK: an integrated system architecture for intraoperative cone-beam CT-guided surgery, Int J Comput Assist Radiol Surg, 7, 159, 10.1007/s11548-011-0636-7

Reed, 2011, Is there an astronomer in the house?, Science (New York, N.Y.), 331, 696, 10.1126/science.331.6018.696

Fedorov, 2011, Atlas-guided segmentation of vervet monkey brain MRI, Open Neuroimaging J, 5, 186, 10.2174/1874440001105010186

Yeo, 2011, The effect of augmented reality training on percutaneous needle placement in spinal facet joint injections, IEEE Trans Bio-Medical Eng, 58, 2031, 10.1109/TBME.2011.2132131

Xu H, Gage HD, Santago P. An open source implementation of colon CAD in 3D slicer. In: Proceedings of SPIE. Vol. 7624.; 2010. pp. 762421–762421–9.

Washko, 2011, Lung volumes and emphysema in smokers with interstitial lung abnormalities, N Engl J Med, 364, 897, 10.1056/NEJMoa1007285

Chen, 2011, Three-dimensional in vivo modeling of vestibular schwannomas and surrounding cranial nerves with diffusion imaging tractography, Neurosurgery, 68, 1077, 10.1227/NEU.0b013e31820c6cbe

Vatta, 2011, Brain morphometry in autism spectrum disorders: a unified approach for structure-specific statistical analysis of neuroimaging data — Biomed 2011, Biomed Sci Instrum, 47, 135

Ashburner, 2009, Computational anatomy with the SPM software, Magn Reson Imaging, 27, 1163, 10.1016/j.mri.2009.01.006

Yushkevich, 2006, User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability, Neuroimage, 31, 1116, 10.1016/j.neuroimage.2006.01.015

Jiang, 2006, DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking, Comput Methods Programs Biomed, 81, 106, 10.1016/j.cmpb.2005.08.004

Smith, 2004, Advances in functional and structural MR image analysis and implementation as FSL, Neuroimage, 23, S208, 10.1016/j.neuroimage.2004.07.051

Rosset, 2004, OsiriX: an open-source software for navigating in multidimensional DICOM images, J Digit Imaging, 17, 205, 10.1007/s10278-004-1014-6

McAuliffe, 2001, Medical image processing, analysis and visualization in clinical research, 381

Barboriak, 2005, Creation of DICOM-aware applications using Image J, J Digit Imaging, 18, 91, 10.1007/s10278-004-1879-4

Liao W, Deserno TM, Spitzer K. Evaluation of free non-diagnostic DICOM software tools. In: Proceedings of SPIE. Vol. 6919. SPIE; 2008. pp. 691903-691903-12.

Walter, 2010, Visualization of image data from cells to organisms, Nat Methods, 7, S26, 10.1038/nmeth.1431

Rubin, 2009, Annotation and image markup: accessing and interoperating with the semantic content in medical imaging, IEEE Intelligent Syst, 24, 57, 10.1109/MIS.2009.3

Channin, 2010, The caBIG annotation and image markup project, J Digit Imaging, 23, 217, 10.1007/s10278-009-9193-9

Pieper S, Halle M, Kikinis R. 3D Slicer. In: Proc. of the 1st IEEE International Symposium on Biomedical Imaging: From Nano to Macro 2004.; 2004. pp. 632–635.

Mildenberger, 2002, Introduction to the DICOM standard, Eur Radiol, 12, 920, 10.1007/s003300101100

Pieper S, Lorensen B, Schroeder W, Kikinis R. The NA-MIC Kit: ITK, VTK, Pipelines, Grids and 3D Slicer as An Open Platform for the Medical Image Computing Community. In: 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006. IEEE; 2006. pp. 698-701.

Ibanez L, Schroeder W. The ITK Software Guide 2.4. Kitware, Inc. 2005 p. 804.

Estépar, 2007, Towards scarless surgery: an endoscopic ultrasound navigation system for transgastric access procedures, Comput Aided Surg, 12, 311, 10.1080/10929080701746892

Perona, 1990, Scale-space and edge detection using anisotropic diffusion, IEEE Trans Pattern Anal Mach Intell, 12, 629, 10.1109/34.56205

Tustison, 2010, N4ITK: improved N3 bias correction, IEEE Trans Med Imaging, 29, 1310, 10.1109/TMI.2010.2046908

Horn, 1988, Closed-form solution of absolute orientation using orthonormal matrices, J Opt Soc Am, 5, 1127, 10.1364/JOSAA.5.001127

Wells, 1996, Multi-modal volume registration by maximization of mutual information, Med Image Anal, 1, 35, 10.1016/S1361-8415(01)80004-9

Mattes, 2003, PET-CT image registration in the chest using free-form deformations, IEEE Trans Med Imaging, 22, 120, 10.1109/TMI.2003.809072

Karasev P, Malcolm J, Niethammer M, Kikinis R, Tannenbaum A. User-driven 3D mesh region targeting. Imaging. 2010;7625:762513-762513-8.

Pichon, 2004, A statistically based flow for image segmentation, Med Image Anal, 8, 267, 10.1016/j.media.2004.06.006

Gao, 2011, Medical computer vision. Recognition techniques and applications in medical imaging, 195

Veeraraghavan H, Miller JV. Active learning guided interactions for consistent image segmentation with reduced user interactions. In: 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE; 2011. pp. 1645-1648.

Wells, 1996, Adaptive segmentation of MRI data, IEEE Trans Med Imaging, 15, 429, 10.1109/42.511747

Pohl, 2007, A hierarchical algorithm for MR brain image parcellation, IEEE Trans Med Imaging, 26, 1201, 10.1109/TMI.2007.901433

Basser, 2000, In vivo fiber tractography using DT-MRI data, Magn Reson Med, 44, 625, 10.1002/1522-2594(200010)44:4<625::AID-MRM17>3.0.CO;2-O

Tokuda, 2009, OpenIGTLink: an open network protocol for image-guided therapy environment, Int J Med Robotics Comput Assist Surg MRCAS., 5, 423, 10.1002/rcs.274

Oliphant, 2007, Python for scientific computing, Comput Sci Eng, 9, 10, 10.1109/MCSE.2007.58

Eads, 2008, Experiences using SciPy for computer vision research, 22

Pierson, 2011, Fully automated analysis using BRAINS: AutoWorkup, Neuroimage, 54, 328, 10.1016/j.neuroimage.2010.06.047

Gorgolewski, 2011, Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python, Front Neuroinformatics, 5, 15

Turkbey, 2010, Prostate cancer: value of multiparametric MR imaging at 3 T for detection–histopathologic correlation, Radiology, 255, 89, 10.1148/radiol.09090475

Hoeks, 2011, Prostate cancer: multiparametric MR imaging for detection, localization, and staging, Radiology, 261, 46, 10.1148/radiol.11091822

Fennessy, 2011, A comparison between arterial input function approaches for high temporal resolution pharmacokinetic analysis of prostate cancer at 3.0T, Vol. 17, 3064

Fennessy, 2012, Assessment of abnormal ADC matched voxels with DCE parameters for characterization of prostate cancer at 3T, Vol. 2

Fedorov, 2011, Hierarchical image registration for improved sampling during 3T MRI-guided transperineal targeted prostate biopsy, Vol. 29, 3055

Fedorov, 2012, Deformable registration for recovering image distortions in DWI MRI of the prostate at 3T, Vol. 256

Clunie, 2007, DICOM structured reporting and cancer clinical trials results, Cancer Inf, 4, 33, 10.4137/CIN.S37032

Wahl, 2009, From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors, J Nucl Med, 50, 122S, 10.2967/jnumed.108.057307

Boellaard, 2009, Standards for PET image acquisition and quantitative data analysis, J Nucl Med, 50, 11S, 10.2967/jnumed.108.057182

Tomasi, 2011, Importance of quantification for the analysis of PET data in oncology: review of current methods and trends for the future, Mol Imaging Biol, 13, 1

Scott, 2010, Bevacizumab salvage therapy following progression in high-grade glioma patients treated with VEGF receptor tyrosine kinase inhibitors, Neuro Oncol, 12, 603, 10.1093/neuonc/nop073

FDA. Oncologic Drugs Advisory Committee — briefing information for the March 31, 2009 meeting of the Oncologic Drugs Advisory Committee. Center for Drug Evaluation and Research; 2009.

Sorensen, 2009, A “vascular normalization index” as potential mechanistic biomarker to predict survival after a single dose of cediranib in recurrent glioblastoma patients, Cancer Res, 69, 5296, 10.1158/0008-5472.CAN-09-0814

Macdonald, 1990, Response criteria for phase II studies of supratentorial malignant glioma, J Clin Oncol, 8, 1277, 10.1200/JCO.1990.8.7.1277

Wen, 2010, Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group, J Clin Oncol, 28, 1963, 10.1200/JCO.2009.26.3541