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  • Ganesan P, Rajaraman S, Long LR, Ghoraani B, Antani SK. Assessment of Data Augmentation Strategies Toward Performance Improvement of Abnormality Classification in Chest Radiographs. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, 23 – 27 July 2019. pp. 841 – 844.
  • Ganesan P, Xue Z, Singh S, Long LR, Ghoraani B, Antani SK. Performance Evaluation of a Generative Adversarial Network for Deblurring Mobile-phone Cervical Images. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, 23 – 27 July 2019. pp. 4487 – 4490.
  • Rajaraman S, Sornapudi S, Kohli M, Antani SK. Assessment of an ensemble of machine learning models toward abnormality detection in chest radiographs. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, 23 – 27 July 2019. pp. 3689 – 3692.
  • Kim J, Tran L, Chew E, Antani SK. Optic Disc and Cup Segmentation for Glaucoma Characterization Using Deep Learning 2019 IEEE 32th International Symposium on Computer-Based Medical Systems (CBMS), pp 489-494, Cordoba, Spain, June 2019.
  • Ben Abacha A, Demner-Fushman D. On the Role of Question Summarization and Information Source Restriction in Consumer Health Question Answering. Proceedings of the AMIA 2019 Informatics Summit, San Francisco, CA, USA, March 25-28, 2019.
  • Kim J, Tran L, Chew E, Antani SK, Thoma GR. Optic Disc Segmentation in Fundus Images Using Deep Learning. SPIE Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, Vol. 10954, San Diego, USA, February 2019.
  • 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.
  • Candemir S, Rajaraman S, Thoma GR, Antani SK. Deep Learning for Grading Cardiomegaly Severity in Chest X-rays: An Investigation. Proc. IEEE Life Sciences Conference (LSC 2018), Montreal, Quebec, Canada, 28 – 30 October 2018. pp. 109-113.
  • Moallem G, Sari-Sarraf H, Poostchi Mohammadabadi M, Maude R, Silamut K, Antani SK, Jaeger S. Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears. SPIE Medical Imaging, 2018.
  • Ben Abacha A, Gayen S, Lau JJ, Rajaraman S, Demner-Fushman D. NLM at ImageCLEF 2018 Visual Question Answering in the Medical Domain. CLEF2018 Working Notes. CEUR Workshop Proceedings, Avignon, France, CEUR-WS.org (September 10-14 2018).
  • Rajaraman S, Candemir S, Xue Z, Alderson P, Kohli M, Abuya J, Thoma GR, Antani SK. A novel stacked generalization of models for improved TB detection in chest radiographs. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC 2018), Honolulu, Hawaii, 2018. pp. 718-721.
  • Xue Z, Long LR, Jaeger S, Folio L, Thoma GR. Extraction of Aortic Knuckle Contour in Chest Radiographs Using Deep Learning. EMBC 2018.
  • Xue Z, Rajaraman S, Long LR, Antani SK, Thoma GR. Gender Detection from Spine X-ray Images Using Deep Learning. Proc. IEEE International Symposium on Computer-Based Medical Systems (CBMS), Karlstad, Sweden, 2018. pp. 54-58, DOI:10.1109/CBMS.2018.00017.
  • Kim J, Candemir S, Chew E, Thoma GR. Region of Interest Detection in Fundus Images Using Deep Learning and Blood Vessel Information. The 31th IEEE International Symposium on Computer-Based Medical Systems. (IEEE CBMS 2018), pp. 357-362, Karlstad, Sweden, June 2018.
  • Xue Z, Jaeger S, Antani SK, Long LR, Karargyris A, Siegelman J, Folio L, Thoma GR. Localizing tuberculosis in chest radiographs with deep learning. Proc SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 105790U (6 March 2018) pp. doi: 10.1117/12.2293022
  • 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.
  • Zohora FT, Antani SK, Santosh KC. Circle-like foreign element detection in chest x-rays using normalized cross-correlation and unsupervised clustering. Proc. SPIE 10574, Medical Imaging 2018: Image Processing, 105741V (2 March 2018); doi: 10.1117/12.2293739; doi.org/10.1117/12.2293739.
  • Rajaraman S, Antani SK, Candemir S, Xue Z, Abuya J, Kohli M, Alderson P, Thoma GR. Comparing deep learning models for population screening using chest radiography. Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105751E (27 February 2018).
  • Xue Z, Jaeger S, Antani SK, Long LR, Karargyris A, Siegelman J, Folio LR, Thoma GR. Localizing tuberculosis in chest radiographs with deep learning. SPIE Medical Imaging 2018
  • Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. SPIE Medical Imaging 2018
  • Bryant B, Sari-Sarraf H, Long LR, Antani SK. A Kernel Support Vector Machine Trained Using Approximate Global and Exhaustive Local Sampling. Proceedings of the 4th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT) 2017, Austin, Texas, USA, December 2017. Pp. 267-8 DOI: https://doi.org/10.1145/3148055.3149206
  • de Herrera G, Long LR, Antani SK. Graph Representation for Content–based fMRI Activation Map Retrieval. Proceedings of 1st Life Sciences Conference, Sydney, Australia, December 2017 pp. 129-32 DOI: https://doi.org/10.1109/LSC.2017.8268160.
  • 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.
  • Almubarak HA, Stanley RJ, Long LR, Antani SK, Thoma GR, Zuna R, Frazier SR. Convolutional Neural Network Based Localized Classification of Uterine Cervical Cancer Digital Histology Images. Procedia Computer Science, Volume 114, 2017, Pages 281-287, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2017.09.044.
  • 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.

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