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  • Xue Z, Long LR, Antani SK, Jeronimo J, Thoma GR. Segmentation of Mosaicism in Cervicographic Images Using Support Vector Machines Proc. SPIE 7259, Medical Imaging 2009, Lake Buena Vista, Florida, United States: Image Processing, 72594X (27 March 2009); doi: 10.1117/12.812318;
  • Xue Z, Long R, Antani SK, Thoma GR. A Web-accessible Content-based Cervicographic Image Retrieval System Proc SPIE Medical Imaging 2008. April 2008;6919:691907-1-9
  • Xue Z, Antani SK, Long LR, Thoma GR. Comparative Performance Analysis of Cervix ROI Extraction and Specular Reflection Removal Algorithms for Uterine Cervix Image Analysis Proc SPIE Medical Imaging 2007. Vol. 6512: 65124I-1-9
  • Xue Z, Antani S, Long LR, Jeronimo J, Thoma GR. Investigating CBIR Techniques for Cervicographic Images AMIA Annu Symp Proc. 2007 Oct 11:826-30.
  • Yang F, Quizon N, Silamut K, Maude RJ, Jaeger S, Antani SK. Cascading YOLO: Automated Malaria Parasite Detection for Plasmodium Vivax in Thin Blood Smears. To be presented at SPIE Medical Imaging, Feb.18-20, 2020, Houston, USA.
  • Yang F, Poostchi M, Silamut K, Maude RJ, Jaeger S, Thoma G. Automated Parasite Classification of Malaria on Thick Blood Smears. ASTMH 67th Annual Meeting, New Orleans, LA, Oct. 28 – Nov. 1, 2018.
  • Yang F, Yu H, Silamut K, Maude RJ, Jaeger S, Antani SK. Parasite Detection in Thick Blood Smears Based on Customized Faster-RCNN. Proceedings of AIPR2019, Washington DC, USA, Oct 15-17, 2019.
  • Yang F, Yu H, Silamut K, Maude R, Jaeger S, Antani SK. Smartphone-Supported Malaria Diagnosis Based on Deep Learning. Proceedings of 10th Workshop on Machine Learning in Medical Imaging (MLMI 2019) in conjunction with MICCAI, Shenzhen, China, Oct 13-17, 2019.
  • Yang F, Yu H, Silamut K, Maude RJ, Jaeger S, Antani SK. Smartphone-Supported Malaria Diagnosis Based on Deep Learning. In: Suk HI., Liu M., Yan P., Lian C. (eds) Machine Learning in Medical Imaging. MLMI 2019. Lecture Notes in Computer Science, vol 11861. Springer, Cham.
  • Yang F, Poostchi M, Yu H, Zhou Z, Silamut K, Yu J, Maude RJ, Jaeger S, Antani SK. Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears. IEEE J Biomed Health Inform. 2019 Sep 23. doi: 10.1109/JBHI.2019.2939121.
  • Yang F, Yu H, Poostchi M, Silamut K, Maude RJ, Jaeger S. Smartphone-Supported Automated Malaria Parasite Detection. SIIM conference on Machine Intelligence in Medical Imaging, 2018.
  • Yang S, Guo J, King PS, Sriraja Y, Long LR. Multispectral Digital Cervigram Analyser in the Wavelet Domain for Early Detection of Cervical Cancer Proc. SPIE Medical Imaging. 2004 Feb; 5370.
  • Yaniv Z, Lowekamp B, Johnson HJ, Beare R. SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research. J Digit Imaging. 2018 Jun;31(3):290-303. doi: 10.1007/s10278-017-0037-8.
  • Yaniv Z. Registration for Orthopaedic Interventions. Chapter 3 in: Zheng G, Li S, editors. Computational Radiology for Orthopaedic Interventions: Lecture Notes in Computational Vision and Biomechanics. Springer International Publishing; c2016. p. 41-70.
  • Yaniv Z, Linte CA. Applications of Augmented Reality in the Operating Room. Chapter 19 in Fundamentals of Wearable Computers and Augmented Reality, 2nd ed. CRC Press, 2015.
  • Yaniv Z, Holmes DR III, editors. Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling. Proceedings of conference held 2014 Feb 15-20; San Diego. Proc. SPIE 9036; 2014 Mar 12. 764 pages. ISBN: 9780819498298.
  • Yao J, Antani S, Long LR, Thoma GR, Zhang Z. Automatic Medical Image Annotation and Retrieval Using SECC Proc CBMS 2006, June 2006, Salt Lake City, Utah; 105-10
  • Yoo T, Ackerman MJ, Lorensen W, Schroeder W, Chalana V, Aylward S, Metaxas D, Whitaker R. Engineering and Algorithm Design for an Image Processing API: A Technical Report on ITK - The Insight Toolkit. In: Westwood JD, Hoffman HM, Robb RA, Stredney D, editors. Stud Health Technol Inform [Studies in Health Technology and Informatics] -- Proceedings of the 10th annual Medicine Meets Virtual Reality conference – Digital Upgrades: Applying Moore’s Law to Health; 2002 Jan 23-26; Newport Beach, California;85:586-92. Amsterdam: IOS Press.
  • 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.
  • Yoo TS, Hamilton T, Hurt D, Caban J, Liao D, Chen D. Toward Quantitative X-Ray CT Phantoms of Metastatic Tumors Using Rapid Prototyping Technology. In: Pan X, Liebling M, editors. Proceedings of ISBI 2011: IEEE Computer Society International Symposium on Biomedical Imaging: From Nano to Macro; 2011 Mar 30-Apr 2; Chicago. p. 1770-3. DOI: 10.1109/ISBI.2011.5872749.
  • 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.
  • Yoo TS, Rheingans P, Chen D, Olano M, Lowekamp B. Animated embroidery: a teapot in modern blackwork. ACM SIGGRAPH 2006 Teapot Exhibit entry; 2006 Jul 30-Aug 3; Boston.
  • Yoo TS. 3D Medical Informatics: Information Science in Multiple Dimensions. In: Chen H, Fuller SS, Friedman C, Hersh W, editors. Medical Informatics: Knowledge Management and Data Mining in Biomedicine. New York: Springer Science. p. 333-58.
  • Yoo TS. The Insight Toolkit: An Open-Source Initiative in Data Segmentation and Registration. In: Johnson C, Hansen C, editors. The Visualization Handbook. Amsterdam: Elsevier; 2005. p. 733-48.
  • Yoo TS, Metaxas DN. Open science – combining open data and open source software: Medical image analysis with the Insight Toolkit. Med Image Anal. 2005 Dec;9(6):503-6. Epub 2005 Sep 19.