no code implementations • 21 Mar 2024 • Saba Heidari Gheshlaghi, Milan Aryal, Nasim Yahyasoltani, Masoud Ganji
In this work, we aim at improving the robustness of cancer Gleason grading classification systems against adversarial attacks, addressing challenges at both the image and graph levels.
no code implementations • 28 Dec 2023 • Dibaloke Chanda, Saba Heidari Gheshlaghi, Nasim Yahya Soltani
A novel explainability-based method is proposed to identify important nodes in the graph and perform edge perturbation between these nodes.
no code implementations • 27 Oct 2023 • Saba Heidari Gheshlaghi, Milan Aryal, Nasim Yahyasoltani, Masoud Ganji
Whole slide images~(WSIs) are digitized images of tissues placed in glass slides using advanced scanners.
no code implementations • 28 Jul 2020 • Saba Heidari Gheshlaghi, Omid Dehzangi, Ali Dabouei, Annahita Amireskandari, Ali Rezai, Nasser M. Nasrabadi
We incorporate the Unet architecture in the NAS framework as its backbone for the segmentation of the retinal layers in our collected and pre-processed OCT image dataset.
no code implementations • 10 Apr 2018 • Saba Heidari Gheshlaghi, Abolfazl Madani, AmirAbolfazl Suratgar, Fardin Faraji
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.