1 citations · 4 across the 12 of their papers we have counts for
4 papers · 1 filter
Hybrid Diffusion Model for Breast Ultrasound Image Augmentation
Farhan Fuad Abir, Sanjeda Sara Jennifer, Niloofar Yousefi +1
We propose a hybrid diffusion-based augmentation framework to overcome the critical challenge of ultrasound data augmentation in breast ultrasound (BUS) datasets. Unlike convention…
Improved Topological Preservation in 3D Axon Segmentation and Centerline Detection using Geometric Assessment-driven Topological Smoothing (GATS)
Nina I. Shamsi, Alex S. Xu, Lars A. Gjesteby +1
Automated axon tracing via fully supervised learning requires large amounts of 3D brain imagery, which is time consuming and laborious to obtain. It also requires expertise. Thus,…
Active Learning Pipeline for Brain Mapping in a High Performance Computing Environment
Adam Michaleas, Lars A. Gjesteby, Michael Snyder +10
This paper describes a scalable active learning pipeline prototype for large-scale brain mapping that leverages high performance computing power. It enables high-throughput evaluat…
Self-Supervised Feature Extraction for 3D Axon Segmentation
Tzofi Klinghoffer, Peter Morales, Young-Gyun Park +3
Existing learning-based methods to automatically trace axons in 3D brain imagery often rely on manually annotated segmentation labels. Labeling is a labor-intensive process and is…