Publications (7)
A Markov Variation Approach to Smooth Graph Signal Interpolation
Ayelet Heimowitz, Yonina C. Eldar
In this paper we present the Markov variation, a smoothness measure which offers a probabilistic interpretation of graph signal smoothness. This measure is then used to develop an…
Bias and variance reduction and denoising for CTF Estimation
Ayelet Heimowitz, Joakim Andén, Amit Singer
When using an electron microscope for imaging of particles embedded in vitreous ice, the objective lens will inevitably corrupt the projection images. This corruption manifests as…
Semi-supervised Learning in Network-Structured Data via Total Variation Minimization
Alexander Jung, Alfred O. Hero, Alexandru Mara +3
We propose and analyze a method for semi-supervised learning from partially-labeled network-structured data. Our approach is based on a graph signal recovery interpretation under a…
APPLE Picker: Automatic Particle Picking, a Low-Effort Cryo-EM Framework
Ayelet Heimowitz, Joakim Andén, Amit Singer
Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult…
Outlier Removal in Cryo-EM via Radial Profiles
Lev Kapnulin, Ayelet Heimowitz, Nir Sharon
The process of particle picking, a crucial step in cryo-electron microscopy (cryo-EM) image analysis, often encounters challenges due to outliers, leading to inaccuracies in downst…
Image Segmentation via Probabilistic Graph Matching
Ayelet Heimowitz, Yosi Keller
This work presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as a inference problem based on unary and pairwise assignment…