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, 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.
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.
Guo P, Singh S, Xue Z, Long LR, Antani SK.Deep Learning for Assessing Image Focus for Automated Cervical Cancer Screening. 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) DOI: 10.1109/BHI.2019.8834495.
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.
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, 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).
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.
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.
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.
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.
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.
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.
Shin HC, Roberts K, Lu L, Demner-Fushman D.Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
Xue Z, Antani SK, Long LR, Demner-Fushman D, Thoma GR.Improving face image extraction by using deep learning technique. Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 97890J (March 25, 2016); doi:10.1117/12.2216278.
Faruque J, Antani SK, Long LR, Kim L, Thoma GR.Image similarity ranking of focal computed tomography liver lesions using a 2AFC technique. Proc. SPIE. 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97870N. DOI: 10.1117/12.2217364.
Xue Z, Candemir S, Antani SK, Long LR, Jaeger S, Demner-Fushman D, Thoma GR.Foreign Object Detection in Chest X-rays. Proc IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2015, International Workshop on Biomedical and Health Informatics, Bethesda, Maryland, Nov. 9-12, 2015, pp: 56-61.
Xu T, Xin C, Long LR, Antani SK, Xue Z, Kim E, Huang X.A New Image Data Set and Benchmark for Cervical Dysplasia Classification Evaluation. Machine Learning in Medical Imaging: 6th International Workshop, MLMI 2015, LNCS 9352, pp. 26–35, 2015. DOI: 10.1007/978-3-319-24888-2 4.