You are here

  • 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.
  • Mundkur ML, McDonald CJ. Utilizing Medicare claims for the assessment of influenza vaccination coverage in the US elderly. J Gen Intern Med, 2016. 31: p. S463.
  • 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.
  • 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.
  • Du H, Yoo TS. Visualizing Indexing Similarity Over the NLM Medical Subject Headings (MeSH). IEEE InfoVis [Information Visualization] 2007 Conference; 2007 Oct 28-30; Sacramento, California.
  • Yoo TS, Silver D, Correa C, Chen D, Moran A. Volumetric Bodies - the Exhibition. IEEE VisWeek 2009 Interactive Demo & Art Exhibit; 2009 Oct 12-16; Atlantic City, New Jersey.
  • 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
  • Zhu Y, Long LR, Antani S, Xue Z, Thoma GR. Web-based STAPLE for Quality Estimation of Multiple Image Segmentations Poster at 20th NIH Research Festival (IMAG-12), September 2007, National Institutes of Health
  • Linte CA, Yaniv Z. When change happens: computer assistance and image guidance for minimally invasive therapy. Healthcare Technology Letters. 2014 Mar 25;1(1):2-5.
  • Moallem G, Jaeger S, Poostchi M, Palaniappan N, Yu H, Silamut K, Maude RJ, Antani SK, Thoma GR. White Blood Cell Detection and Segmentation in Microscopy Images of Thin Blood Smears [Poster]. NIH Research Festival, Poster, 2017
  • Xue Z, Antani SK, Long LR, Demner-Fushman D, Thoma GR. Window classification of brain CT images in biomedical articles. AMIA Annu Symp Proc. 2012;2012:1023-9. Epub 2012 Nov 3.

Pages