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  • Goedert JJ, Scoppio BM, Pfeiffer R, Neve L, Federici AB, Long LR, Dolan BM, Brambati M, Bellinvia M, Lauria C, Preiss L, Boneschi V, Whitby D, Brambilla L. Treatment of classic Kaposi sarcoma with a nicotine dermal patch: a phase II clinical trial. phase II clinical trial. J Eur Acad Dermatol Venereol. 2008 Sep;22(9):1101-9. doi: 10.1111/j.1468-3083.2008.02720.x. Epub 2008 Apr 1.r 1.
  • Ren H, Campos-Nanez E, Yaniv Z, Banovac F, Abeledo H, Hata N, Cleary K. Treatment planning and image guidance for radiofrequency ablation of large tumors. IEEE J Biomed Health Inform. 2014 May;18(3):920-8. doi: 10.1109/JBHI.2013.2287202. Epub 2013 Oct 24.
  • Jaeger S, Antani S, Thoma GR. Tuberculosis Screening of Chest Radiographs. 2 June 2011, SPIE Newsroom. DOI: 10.1117/2.1201105.003732i.
  • Jaeger S, Candemir S, Antani SK, Wang Y, Lu P, Thoma GR. Two public chest X-ray datasets for computer-aided screening of pulmonary diseases. Quant Imaging Med Surg. 2014 Dec;4(6):475-7. doi: 10.3978/j.issn.2223-4292.2014.11.20.
  • Rajaraman S, Silamut K, Hossain MA, Ersoy I, Maude RJ, Jaeger S, Thoma GR, Antani SK. Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images. J Med Imaging (Bellingham). 2018 Jul;5(3):034501. doi: 10.1117/1.JMI.5.3.034501. Epub 2018 Jul 18.
  • Long LR, Thoma GR. Use of Shape Models to Search Digitized Spine X-Rays IEEE Computer-Based Medical Systems. 2000 June;: 255-60.
  • Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. Proc SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 105790D (6 March 2018) pp. doi: 10.1117/12.2293027.
  • Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. SPIE Medical Imaging 2018
  • Xu X, Lee DJ, Antani SK, Long LR, Archiband JK. Using Relevance Feedback with Short-term Memory for Content-based Spine X-ray Image Retrieval. J Neurocomputing. June 2009;72(10-12):2259-69.
  • Rondonotti E, Koulaouzidis A, Karargyris A, Giannakou A, Fini L, Soncini M, Pennazio M, Douglas S, Shams A, Lachlan N, Zahid A, Mandelli G, Girelli C. Utility of 3-dimensional image reconstruction in the diagnosis of small-bowel masses in capsule endoscopy (with video). Gastrointest Endosc. 2014 Oct;80(4):642-51. doi: 10.1016/j.gie.2014.04.057. Epub 2014 Jul 3.
  • Ducut E, Liu F, Avila JM, Encinas MA, Diwa M, Fontelo P. Virtual Microscopy in a Developing Country: A Collaborative Approach to Building an Image Library. Journal of eHealth Technology and Application. 2010 Sep;8(2):112-5.
  • Fontelo P, DiNino E, Johansen K, Khan A, Ackerman MJ. Virtual Microscopy: Potential Applications in Medical Education and Telemedicine in Countries with Developing Economies. Proceedings of the 38th Hawaii International Conference on System Sciences; 2005 Jan 3-6; Big Island, Hawaii: 7 pages. IEEE Computer Society.
  • Ratiu P, Hillen B, Glaser J, Jenkins DB. Visible Human 2.0 - The Next Generation. In: Westwood JD, Hoffman HM, Mogel GT, Phillips R, Robb RA, Stredney D, editors. Stud Health Technol Inform [Studies in Health Technology and Informatics] -- Proceedings of the 11th annual Medicine Meets Virtual Reality conference; 2003 Jan;94:275-81. Amsterdam: IOS Press.
  • Ackerman MJ. Visible Human Project. McGraw-Hill 2004 Yearbook of Science & Technology. New York: McGraw-Hill. 2004. p. 369-72.
  • Ackerman MJ. Visible Human Project: From Data to Knowledge. In: Haux R, Kulikowski C, editors. Yearbook of Medical Informatics 2002: Medical Imaging Informatics. International Medical Informatics Association (IMIA). p. 115-7.
  • Jeronimo J, Massad LS, Schiffman M for the NIH-ASCCP Research Group. Visual Appearance of the Uterine Cervix: Correlation with Human Papillomavirus Detection and Type Am J Obstet Gynecol. 2007 Jul;197(1):47.e1-8
  • Kim I, Rajaraman S, Antani SK. Visual Interpretation of Convolutional Neural Network Predictions in Classifying Medical Image Modalities. Diagnostics (Basel). 2019 Apr 3;9(2). pii: E38. doi: 10.3390/diagnostics9020038.
  • Moorhead R, Johnson C, Munzner T, Pfister H, Rheingans P, Yoo TS. Visualization Corner: Visualization Research Challenges: A Report Summary. IEEE Computing in Science and Engineering. 2006 Jul-Aug;8(4):66-73. DOI: 10.1109/MCSE.2006.77.
  • Munzner T, Johnson C, Moorhead R, Pfister H, Rheingans P, Yoo TS. Visualization Viewpoints: NIH-NSF Visualization Research Challenges Report Summary. IEEE Computer Graphics and Applications. 2006 Mar-Apr;26(2):20-24.
  • Rajaraman S, Antani SK, Xue Z, Candemir S, Jaeger S, Thoma GR. Visualizing abnormalities in chest radiographs through salient network activations in Deep Learning. Proc. IEEE Life Sciences Conference (LSC), Sydney, Australia, 2017. pp. 71-74, DOI:10.1109/LSC.2017.8268146.
  • Rajaraman S, Candemir S, Thoma G, Antani SK. Visualizing and explaining deep learning predictions for pneumonia detection in pediatric chest radiographs. Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109500S (13 March 2019); doi: 10.1117/12.2512752.
  • Yoo TS, Bliss D, Lowekamp B, Chen D, Murphy GE, Narayan K, Hartnell LM, Do T, Subramaniam S. Visualizing cells and humans in 3D: Biomedical image analysis at nanometer and meter scales. IEEE Computer Graphics and Applications. 2012 Sep-Oct;32(5):39-49. DOI: 10.1109/MCG.2012.68.
  • Rajaraman S, Antani SK, Jaeger S. Visualizing Deep Learning Activations for Improved Malaria Cell Classification. Proceedings of The First Workshop in Medical Informatics and Healthcare (MIH 2017), Proceedings of Machine Learning Research (PMLR), v. 69, p. 40-47.
  • Xue Z, Antani S, Long LR, Thoma GR. Web-accessible Cervigram Automatic Segmentation Tool SPIE Medical Imaging Conference. March 2010;7628
  • Zhu Y, Huang X, Lopresti D, Long R et al. Web-based Multi-observer Segmentation Evaluation Tool Proc. 21st IEEE CBMS. Jyvaskyla, Finland. June 2008:167-9

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