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  • 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).
  • Vajda S, Karargyris A, Jaeger S, Santosh KC, Candemir S, Xue Z, Antani SK, Thoma GR. Feature Selection for Automatic Tuberculosis Screening in Frontal Chest Radiographs. J Med Syst. 2018 Jun 29;42(8):146. doi: 10.1007/s10916-018-0991-9.
  • 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.
  • 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.
  • Thamizhvani TR, Lakshmanan S, Rajaraman S. Mobile application-based computer-aided diagnosis of skin tumours from dermal images. The Imaging Science Journal, 66:6, 382-391, 2018, DOI: 10.1080/13682199.2018.1492682
  • 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.
  • 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.
  • Sornapudi S, Stanley RJ, Stoecker WV, Almubarak H, Long LR, Antani SK, Thoma GR, Zuna R, Frazier SR. Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels. J Pathol Inform. 2018 Mar 5;9:5. doi: 10.4103/jpi.jpi_74_17. eCollection 2018.
  • Santosh KC, Antani SK. Automated chest x-ray screening: Can lung region symmetry help detect pulmonary abnormalities? doi: 10.1109/TMI.2017.2775636 vol. 37, no. 5, 1168-1177.
  • Rajaraman S, Antani SK, Poostchi Mohammadabadi M, Silamut K, Hossain MA, Maude RJ, Jaeger S, Thoma GR. Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images. PeerJ. 2018 Apr 16;6:e4568. doi: 10.7717/peerj.4568. eCollection 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.
  • 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).
  • 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).
  • 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
  • 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
  • Poostchi M, Silamut K, Maude RJ, Jaeger S, Thoma GR. Image analysis and machine learning for detecting malaria. Transl Res. 2018 Apr;194:36-55. doi: 10.1016/j.trsl.2017.12.004. Epub 2018 Jan 12.
  • 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.
  • Chatain GP, Patronas N, Smirniotopoulos J, James G, Piazza M, Benzo S, Ray-Chaudrury A, Sharma S, Lodish M, Nieman L, Stratakis CA, Chittiboina P. Potential utility of FLAIR in MRI-negative Cushing's disease. J Neurosurg. 2017 Oct 13:1-9. doi: 10.3171/2017.4.JNS17234.
  • Moallem G, Poostchi M, Yu H, Silamut K, Palaniappan N, Antani SK, Hossain Md Amir, Maude RJ, Jaeger S, Thoma GR. Detecting and Segmenting White Blood Cells in Microscopy Images of Thin Blood Smears. Applied Imagery Pattern Recognition Workshop (AIPR), 2017
  • Guan Y, Li M, Jaeger S, Lure F, Raptopoulos V, Lu P, Folio LR, Candemir S, Antani SK, Siegelman J, Li J, Wu T, Thoma GR, Qu S. Applying Artificial Intelligence and Radiomics for Computer Aided Diagnosis and Risk Assessment in Chest Radiographs. 2nd Conference on Machine Intelligence in Medical Imaging (CMIMI) of the Society for Imaging Informatics in Medicine (SIIM), Poster, 2017.
  • Coakley M, Hurt D, Weder N, Mtingwa M, Fincher EC, Alekseyev V, Chen D, Yun A, Gizaw M, Swan J, Yoo TS, Huyen Y. The NIH 3D Print Exchange: A Public Resource for Bioscientific and Biomedical 3D Prints 3D Print Additive Manufacturing, Sep. 1, 2014, 1(3):137-140.
  • 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.
  • Candemir S, Antani SK, Xue Z, Thoma GR. Novel Method for Storyboarding Biomedical Videos for Medical Informatics. 30th IEEE International Symposium on Computer-Based Medical Systems
  • Ding M, Antani SK, Jaeger S, Xue Z, Candemir S, Kohli M, Thoma GR. Local-Global Classifier Fusion for Screening Chest Radiographs. Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 101380A (March 13, 2017); doi:10.1117/12.2252459
  • Xue Z, Antani SK, Long LR, Thoma GR. Automatic multi-label annotation of abdominal CT images using CBIR. Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 1013807 (March 13, 2017); doi:10.1117/12.2254368.
  • Lure F, Jaeger S, Antani SK. Automated Systems for microscopic and radiographic tuberculosis screening. Electronic Journal of Emerging Infectious Diseases, Vol. 2, No. 1, pp. 5-9, February 2017. [In Chinese]
  • KC S, Antani SK. Automated chest X-ray screening: Can lung region symmetry help detect pulmonary abnormalities? IEEE Transactions on Medical Imaging. doi: https://doi.org/10.1109/TMI.2017.2775636.
  • KC S, Aafaque A, Antani SK, Thoma GR. Line Segment-Based Stitched Multipanel Figure Separation for Effective Biomedical CBIR. Int. J. Patt. Recogn. Artif. Intelligence 31, 1757003 (2017) https://doi.org/10.1142/S0218001417570038.
  • Guo P, Almubarak H, Banerjee K, Stanley RJ, Long LR, Antani SK, Thoma GR, Zuna R, Frazier S, Moss R, Stoecker W. Enhancements in localized classification for uterine cervical cancer digital histology image assessment. J Pathol Inform. 2016 Dec 30;7:51. doi: 10.4103/2153-3539.197193. eCollection 2016.
  • 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.
  • De Herrera A, Long LR, Antani SK. Content-Based fMRI Brain Maps Retrieval. International Conference on Brain and Health Informatics, Omaha, NE, USA, October 13-16, 2016.
  • Ben Abacha A, de Herrera A, Wang Ke, Long LR, Antani SK, Demner-Fushman D. Named entity recognition in functional neuroimaging literature. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, 2017, pp. 2218-2220.
  • Liang Z, Powell A, Ersoy I, Poostchi M, Silamut K, Palaniappan K, Guo P, Hossain M, Antani SK, Maude R, Huang J, Jaeger S, Thoma GR. CNN-Based Image Analysis for Malaria Diagnosis. IEEE International Conference on Bioinformatics & Biomedicine (BIBM), Shenzhen, China, 2016.
  • Guo P, Stanley RJ, De S, Long LR, Antani SK, Thoma GR, Demner-Fushman D, Sornapudia S. Features Advances to Automatically Find Images for Application to Clinical Decision Support. Medical Research Archives. 4(7) 2016. DOI: 10.18103/mra.v4i7.761
  • Linte CA, Yaniv Z. Image-Guided Interventions: We've come a long way, but are we there? IEEE Pulse. 2016 Nov-Dec;7(6):46-50.
  • 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
  • Mrabet Y, Vougiouklis P, Kilicoglu H, Gardent C, Demner-Fushman D, Hare J, Simperl E. Aligning Texts and Knowledge Bases with Semantic Sentence Simplification. WebNLG 2016.
  • KC S, Vajda S, Antani S, Thoma GR. Edge map analysis in chest X-rays for automatic pulmonary abnormality screening. Int J Comput Assist Radiol Surg. 2016 Sep;11(9):1637-46. doi: 10.1007/s11548-016-1359-6. Epub 2016 Mar 19.
  • Xu T, Zhang H, Xin C, Kim E, Long LR, Xue Z, Antani SK, Huang Z. Multi-feature based Benchmark for Cervical Dysplasia Classification Evaluation. Pattern Recognition. ISSN 0031-3203, DOI: 10.1016/j.patcog.2016.09.027.

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