Jakob Troidl

The paper introduces niiv, a self-supervised method for isotropic reconstruction of 3D microscopy data, achieving faster and higher-quality results than existing methods.

MoMo is an interactive visualization framework that analyzes neuron morphology-aware motifs in connectomes, enabling efficient subgraph isomorphism searches and intuitive exploration through a sketch-based interface.

SynAnno is an interactive tool that streamlines synaptic annotation proofreading in connectomics by integrating guided workflows and machine learning assistance, improving efficiency and reducing errors.

The paper presents a connectomic dataset of a larval zebrafish brain, enabling circuit analysis through synaptic and neuronal annotations.

CAVE enables reproducible connectome analysis in large-scale datasets during ongoing annotation and proofreading.

This paper introduces a point affinity transformer framework for global neuron shape reasoning, improving segmentation error correction and neuron type classification in connectomics.

psudo is an interactive system that optimizes pseudocolor palettes for multichannel biomedical images to enhance perceptual distinction and reduce color confusion in overlapping channels.

The paper presents a connectomic analysis of a human cerebral cortex fragment, revealing structural and connectivity features of neurons and synapses.

Vimo enables interactive visualization of neuronal connectivity motifs in large brain networks, allowing experts to sketch and analyze motif instances and chains in 3D.

The paper discusses challenges in digital image analysis of cancerous tissues and outlines solutions developed during a 2022 hackathon.

This paper introduces a method for saturated reconstruction of living brain tissue using advanced imaging and deep learning to achieve high-resolution, volumetric analysis of neural structures over time.