no code implementations • 15 Jan 2024 • Antoine Mercier, Ramin Nakhli, Mahesh Reddy, Rajeev Yasarla, Hong Cai, Fatih Porikli, Guillaume Berger
Despite the latest remarkable advances in generative modeling, efficient generation of high-quality 3D assets from textual prompts remains a difficult task.
no code implementations • 8 Mar 2023 • Ramin Nakhli, Allen Zhang, Hossein Farahani, Amirali Darbandsari, Elahe Shenasa, Sidney Thiessen, Katy Milne, Jessica McAlpine, Brad Nelson, C Blake Gilks, Ali Bashashati
To showcase the potential power of our proposed framework, we applied VOLTA to ovarian and endometrial cancers with very small sample sizes (10-20 samples) and demonstrated that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide novel insights that link histopathology and molecular subtypes of endometrial cancer.
1 code implementation • 1 Mar 2023 • Ramin Nakhli, Puria Azadi Moghadam, Haoyang Mi, Hossein Farahani, Alexander Baras, Blake Gilks, Ali Bashashati
Processing giga-pixel whole slide histopathology images (WSI) is a computationally expensive task.
no code implementations • ICCV 2023 • Ramin Nakhli, Allen Zhang, Ali Mirabadi, Katherine Rich, Maryam Asadi, Blake Gilks, Hossein Farahani, Ali Bashashati
Importantly, our model is able to stratify the patients into different risk cohorts with statistically different outcomes across two large datasets, a task that was previously achievable only using genomic information.
no code implementations • CVPR 2023 • Ramin Nakhli, Puria Azadi Moghadam, Haoyang Mi, Hossein Farahani, Alexander Baras, Blake Gilks, Ali Bashashati
Processing giga-pixel whole slide histopathology images (WSI) is a computationally expensive task.
1 code implementation • 12 Aug 2022 • Ramin Nakhli, Amirali Darbandsari, Hossein Farahani, Ali Bashashati
In this work, we investigated the utility of Self-Supervised Learning (SSL) in cell clustering by proposing the Contrastive Cell Representation Learning (CCRL) model.