Artifact-Tolerant Clustering-Guided Contrastive Embedding Learning for Ophthalmic Images

1 code implementation • 2 Sep 2022 • Min Shi, Anagha Lokhande, Mojtaba S. Fazli, Vishal Sharma, Yu Tian, Yan Luo, Louis R. Pasquale, Tobias Elze, Michael V. Boland, Nazlee Zebardast, David S. Friedman, Lucy Q. Shen, Mengyu Wang

Ophthalmic images and derivatives such as the retinal nerve fiber layer (RNFL) thickness map are crucial for detecting and monitoring ophthalmic diseases (e. g., glaucoma).

Clustering Contrastive Learning +1

Lightweight and Scalable Particle Tracking and Motion Clustering of 3D Cell Trajectories

1 code implementation • 10 Aug 2019 • Mojtaba S. Fazli, Rachel V. Stadler, BahaaEddin Alaila, Stephen A. Vella, Silvia N. J. Moreno, Gary E. Ward, Shannon Quinn

Tracking cell particles in 3D microscopy videos is a challenging task but is of great significance for modeling the motion of cells.

Cell Detection Cell Tracking +1

Unsupervised Discovery of Toxoplasma gondii Motility Phenotypes

1 code implementation • 8 Jan 2018 • Mojtaba S. Fazli, Stephen A. Vella, Silvia N. J. Moreno, Shannon Quinn

Toxoplasma gondii is a parasitic protozoan that causes dis- seminated toxoplasmosis, a disease that afflicts roughly a third of the worlds population.