49 citations · 81 across the 11 of their papers we have counts for
14 papers
CvS: Classification via Segmentation For Small Datasets
Nooshin Mojab, Philip S. Yu, Joelle A. Hallak +1
Deep learning models have shown promising results in a wide range of computer vision applications across various domains. The success of deep learning methods relies heavily on the…
AutoPtosis
Abdullah Aleem, Manoj Prabhakar Nallabothula, Pete Setabutr +2
Blepharoptosis, or ptosis as it is more commonly referred to, is a condition of the eyelid where the upper eyelid droops. The current diagnosis for ptosis involves cumbersome manua…
I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications
Nooshin Mojab, Vahid Noroozi, Abdullah Aleem +8
Data from clinical real-world settings is characterized by variability in quality, machine-type, setting, and source. One of the primary goals of medical computer vision is to deve…
Real-World Multi-Domain Data Applications for Generalizations to Clinical Settings
Nooshin Mojab, Vahid Noroozi, Darvin Yi +4
With promising results of machine learning based models in computer vision, applications on medical imaging data have been increasing exponentially. However, generalizations to com…
Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization
Darvin Yi, Endre Grøvik, Michael Iv +3
We introduce a novel ensembling method, Random Bundle (RB), that improves performance for brain metastases segmentation. We create our ensemble by training each network on our data…
Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives
Darvin Yi, Endre Grøvik, Michael Iv +3
Deep learning has proven to be an essential tool for medical image analysis. However, the need for accurately labeled input data, often requiring time- and labor-intensive annotati…