3 papers
eess.IV2021
ASIST: Annotation-free Synthetic Instance Segmentation and Tracking by Adversarial Simulations
Quan Liu, Isabella M. Gaeta, Mengyang Zhao +6
Background: The quantitative analysis of microscope videos often requires instance segmentation and tracking of cellular and subcellular objects. The traditional method consists of…
eess.IV2020
ASIST: Annotation-free synthetic instance segmentation and tracking for microscope video analysis
Quan Liu, Isabella M. Gaeta, Mengyang Zhao +6
Instance object segmentation and tracking provide comprehensive quantification of objects across microscope videos. The recent single-stage pixel-embedding based deep learning appr…
cs.CV2020
GAN based Unsupervised Segmentation: Should We Match the Exact Number of Objects
Quan Liu, Isabella M. Gaeta, Bryan A. Millis +2
The unsupervised segmentation is an increasingly popular topic in biomedical image analysis. The basic idea is to approach the supervised segmentation task as an unsupervised synth…