Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Gheshlaghi, Saba Heidari"'
Enhancing the robustness of deep learning models against adversarial attacks is crucial, especially in critical domains like healthcare where significant financial interests heighten the risk of such attacks. Whole slide images (WSIs) are high-resolu
Externí odkaz:
http://arxiv.org/abs/2403.14489
Despite the success of graph neural networks (GNNs) in various domains, they exhibit susceptibility to adversarial attacks. Understanding these vulnerabilities is crucial for developing robust and secure applications. In this paper, we investigate th
Externí odkaz:
http://arxiv.org/abs/2312.17301
Whole slide images~(WSIs) are digitized images of tissues placed in glass slides using advanced scanners. The digital processing of WSIs is challenging as they are gigapixel images and stored in multi-resolution format. A common challenge with WSIs i
Externí odkaz:
http://arxiv.org/abs/2310.18192
Autor:
Gheshlaghi, Saba Heidari1 (AUTHOR), Kan, Chi Nok Enoch2 (AUTHOR) kanxx030@gmail.com, Schmidt, Taly Gilat3 (AUTHOR) tal.gilat-schmidt@marquette.edu, Ye, Dong Hye4 (AUTHOR) dongye@gsu.edu
Publikováno v:
Bioengineering (Basel). Apr2024, Vol. 11 Issue 4, p319. 15p.
Autor:
Gheshlaghi, Saba Heidari, Dehzangi, Omid, Dabouei, Ali, Amireskandari, Annahita, Rezai, Ali, Nasrabadi, Nasser M
In this work, we propose a Neural Architecture Search (NAS) for retinal layer segmentation in Optical Coherence Tomography (OCT) scans. We incorporate the Unet architecture in the NAS framework as its backbone for the segmentation of the retinal laye
Externí odkaz:
http://arxiv.org/abs/2007.14790
Autor:
Gheshlaghi, Saba Heidari, Ranjbar, Amin, Suratgar, Amir Abolfazl, Menhaj, Mohammad Bagher, Faraji, Fardin
A Superpixel Segmentation Based Technique for Multiple Sclerosis Lesion Detection
Comment: 11 Pages, Journal Submitted
Comment: 11 Pages, Journal Submitted
Externí odkaz:
http://arxiv.org/abs/1907.03109
Magnetic resonance images (MRI) play an important role in supporting and substituting clinical information in the diagnosis of multiple sclerosis (MS) disease by presenting lesion in brain MR images. In this paper, an algorithm for MS lesion segmenta
Externí odkaz:
http://arxiv.org/abs/1804.03282
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2022 Jul; Vol. 2022, pp. 1891-1894.
Publikováno v:
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2021 Nov; Vol. 2021, pp. 3387-3390.