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Search results for biblio_year:2023
Filters: 1 is field_research_area:1 and Author is Sravanthi Parasa  [Reset Search]
2022
J. A. Fageren, V. Thambawita, A. Storås, S. Parasa, T. de Lange, P. Halvorsen and M. Riegler. PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps In IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2022.
V. Thambawita, P. Salehi, S. A. Sheshkal, S. Hicks, H. L. Hammer, S. Parasa, T. de Lange, P. Halvorsen and M. Riegler. "SinGAN-Seg: Synthetic training data generation for medical image segmentation." PLOS ONE 17, no. 5 (2022): e0267976.PDF icon journal.pone_.0267976.pdf (2.66 MB)
S. Hicks, A. Storås, M. Riegler, C. Midoglu, M. Hammou, T. de Lange, S. Parasa, P. Halvorsen and I. Strümke. Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations. arXiv, 2022.
2021
V. Thambawita, I. Strümke, S. Hicks, M. Riegler, P. Halvorsen and S. Parasa. Data Augmentation Using Generative Adversarial Networks For Creating Realistic Artificial Colon Polyp Images In DDW 2021., 2021.
V. Thambawita, S. Hicks, J. Isaksen, M. H. Stensen, T. B. Haugen, J. Kanters, S. Parasa, T. de Lange, H. D. Johansen, D. Johansen et al. DeepSynthBody: the beginning of the end for data deficiency in medicine In The International Conference on Applied Artificial Intelligence (ICAPAI). IEEE, 2021.
V. Thambawita, S. Hicks, I. Strümke, M. Riegler, P. Halvorsen and S. Parasa. Impact of Image Resolution on Convolutional Neural Networks Performance in Gastrointestinal Endoscopy In DDW 2021., 2021.
V. Thambawita, I. Strümke, S. Hicks, P. Halvorsen, S. Parasa and M. Riegler. "Impact of Image Resolution on Deep Learning Performance in Endoscopy Image Classification: An Experimental Study Using a Large Dataset of Endoscopic Images." Diagnostics 11, no. 12 (2021).PDF icon diagnostics-11-02183_1.pdf (3.38 MB)
S. Hicks, D. Jha, V. Thambawita, H. L. Hammer, T. de Lange, S. Parasa, M. Riegler and P. Halvorsen. Medico Multimedia Task at MediaEval 2021: Transparency in Medical Image Segmentation In Mediaeval Medico 2021. Mediaeval 2021, 2021.