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Shelda Sajeev

  • Source: Scopus
  • Calculated based on no. of publications stored in Pure and citations from Scopus
20132020

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Personal profile

Education/Academic qualification

Image processing and Machine Learning, PhD, Flinders University

Award Date: 26 Jul 2019

Computer Science and Engineering, Master, Visvesvaraya Technological University

Award Date: 10 May 2013

Computer Science and Engineering, Bachelor

Award Date: 20 May 2005

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  • 71 Citations
  • 3 h-Index
  • 9 Conference contribution
  • 1 Chapter
  • 1 Article
  • 1 Review article

  • Mammographic mass identification in dense breasts using multi-scale analysis of structured micro-patterns

    Sajeev, S., Bajger, M., Lee, G., Muramatsu, C. & Fujita, H., 1 Jan 2020, 15th International Workshop on Breast Imaging, IWBI 2020. Bosmans, H., Marshall, N. & Van Ongeval, C. (eds.). SPIE, 1151323. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 11513).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

  • Cardiovascular Risk Prediction Models: A Scoping Review

    Sajeev, S. & Maeder, A., 29 Jan 2019, Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2019. Association for Computing Machinery (ACM), a21. (ACM International Conference Proceeding Series).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    1 Citation (Scopus)

  • Deep Learning to Improve Heart Disease Risk Prediction

    Sajeev, S., Maeder, A., Champion, S., Beleigoli, A., Ton, C., Kong, X. & Shu, M., 1 Jan 2019, Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting - 1st International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI 2019, Proceedings. Liao, H., Wang, G., Liu, Y., Ding, Z., Balocco, S., Zhang, F., Duong, L., Phellan, R., Zahnd, G., Albarqouni, S., Demirci, S., Breininger, K., Moriconi, S. & Lee, S-L. (eds.). Springer Gabler, p. 96-103 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11794 LNCS).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

  • Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram

    Sajeev, S., Bajger, M. & Lee, G., 1 Jan 2019, Graph Learning in Medical Imaging - 1st International Workshop, GLMI 2019, held in Conjunction with MICCAI 2019, Proceedings. Zhang, D., Zhou, L., Jie, B. & Liu, M. (eds.). Springer Gabler, p. 147-154 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11849 LNCS).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    1 Citation (Scopus)

  • Superpixel pattern graphs for identifying breast mass ROIs in dense background: A preliminary study

    Sajeev, S., Bajger, M. & Lee, G., 1 Jan 2018, 14th International Workshop on Breast Imaging (IWBI 2018). Krupinski, E. A. (ed.). SPIE, 107180V. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 10718).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

    2 Citations (Scopus)
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