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  • 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.
  • Rajaraman S, Candemir S, Xue Z, Alderson P, Thoma G, Antani SK. A Novel Stacked Model Ensemble for Improved TB Detection in Chest Radiographs. In Santosh KC et al. (Eds.). Medical Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques. (pp. 1-26). New York, NY: CRC Press, Taylor & Francis Group.
  • Ionescu B, Muller H, Peteri R, Dang-Nguyen DT, Piras L, Riegler M, Tran MT, Lux M, Gurrin C, Cid YD, Liauchuk V, Kovalev V, Ben Abacha A, Hasan SA, Datla V, Liu J, Demner-Fushman D, Pelka O, Friedrich CM, Chamberlain J, Clark C, de Herrera AGS, Garcia N, Kavallieratou E, del Blanco CR, Rodriguez CC, Vasillopoulos N, Karampidis K. Multimedia retrieval in medicine, lifelogging, security and nature. International Conference of the Cross-Language Evaluation Forum for European Languages, Springer, Cham, 358-386, 2019
  • Jaeger S, Antani SK, Rajaraman S, Yang F, Yu H. Malaria Screening: Research into Image Analysis and Deep Learning. Report to the Board of Scientific Counselors September 2018.
  • Almubarak H, Guo P, Stanley RJ, Long LR, Antani SK, Thoma GR. Algorithm Enhancements for Improvement of Localized Classification of Uterine Cervical Cancer Digital Histology Images. in Handbook of Research on Emerging Perspectives on Healthcare Information Systems and Informatics,. IGI Global (Hershey, PA).
  • Thamizhvani TR, Lakshmanan S, Rajaraman S. Computer Aided Diagnosis of Skin Tumours from Dermal Images. Hemanth D., Smys S. (eds) Computational Vision and Bio Inspired Computing. Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham
  • Fallavollita P, Kersten M, Linte CA, Pratt P, Yaniv Z. Guest Editors' Foreword: Special Issue on Augmented Environments for Computer-Assisted Interventions CAI systems enable more precise, safer, and less invasive interventional treatments [Letter]. Healthc Technol Lett. 2017 Oct 27;4(5):149. doi: 10.1049/htl.2017.0078. eCollection 2017 Oct.
  • Jaeger S. Malaria Datasets
  • Candemir S. Chest X-ray Screening System: Segmentation Module – v3
  • Borovikov E, Vajda S. FaceMatch: real-world face image retrieval. In: Santosh K., Hangarge M., Bevilacqua V., Negi A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. 405-419.
  • Borovikov E, Vajda S, Lingappa G, Bonifant MC. Parallel Computing in Face Image Retrieval: Practical Approach to the Real-World Image Search. Multi-Core Computer Vision and Image Processing for Intelligent Applications. IGI Global, 2017. 155-189. Web. 12 Sep. 2016. doi:10.4018/978-1-5225-0889-2.ch006
  • 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.
  • Folio, L, Sigelman, J, Wang, Y, Lu, P, Antani SK, Jaeger S. Automatic Identification and Classification of Tuberculosis Findings on Chest Radiographs for Global Surveillance Programs [Abstract]. Annual Meeting of the American Roentgen Ray Society (ARRS)
  • 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.
  • Antani SK. Automated Detection of Lung Diseases in Chest X-Rays April 2015 Technical Report to the LHNCBC Board of Scientific Counselors
  • Antani SK. Tuberculosis Chest X-ray Image Data Sets
  • Linte CA, Yaniv Z, Fallavollita P, Abolmaesumi P, Holmes DR III, editors. Augmented Environments for Computer-Assisted Interventions 2014: 9th International AE-CAI Workshop. Held in conjunction with MICCAI 2014. 2014 Sep 14; Boston. Lecture Notes in Computer Science, vol. 8678. Springer; 2014. 149 pages.
  • 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.
  • Yoo TS, Ackerman MJ, Chen D, Lowekamp B, Kuybeda O, Santoroski J. 3D Informatics April 2014 Technical Report to the LHNCBC Board of Scientific Counselors.
  • Guler, O, Yaniv Z. A tutorial on image guided therapy. Chapter 11 in: Birkfellner W, editor. Applied Medical Image Processing, Second Edition: A Basic Course. London: CRC Press; 2014. ISBN: 9781466555570.
  • Gordon E, Waisberg M, Ersoy I, Pena M, Jaeger S, Pierce S. The eye as a window to investigate the CNS microvasculature during a dynamic malaria infection (Abstract). Third Annual Seminar on Molecular Imaging of Infectious Diseases, September 23, 2013.
  • Neve L, Long LR, Antani SK. Software: Boundary Marking Tool 2 (BMT2)
  • Lowekamp B, Chen D, Santoroski J, Yaniv Z, Yoo TS. Software: SimpleITK.
  • Thoma GR, Ford G, Demner-Fushman D, Antani SK, Chung M. Software: Panorama
  • Ackerman MJ, Yoo TS. 3D Informatics: High Performance Computing at the Lister Hill Center. Technical Report to the LHNCBC Board of Scientific Counselors; 2007 Sep. 29 pages.

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