Software FZJ-2026-05049

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Code and simulation results of the paper: '3D U-Net Segmentation Improves Root System Reconstruction from 3D MRI Images in Automated and Manual Virtual Reality Work Flows'

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2025

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Abstract: This file contains the code and simulation results supporting the paper:  “3D U-Net Segmentation Improves Root System Reconstruction from 3D MRI Images in Automated and Manual Virtual Reality Work Flows”. DOI: https://doi.org/10.34133/plantphenomics.0076

Keyword(s): neural networks ; root architecture ; environmental modelling ; agriculture ; magnetic resonance imaging ; plant water relations ; hydraulic conductivity


Note: + Grant that is not in the system: SCHN 1361/3-1 Weiterentwicklung funktional-struktureller Modellierung von Wurzelwachstum und Wurzel-Boden-Interaktionen basierend auf automatischer Rekonstruktion von Wurzelsystemen aus MRIDeutsche Forschungsgemeinschaft

Contributing Institute(s):
  1. Agrosphäre (IBG-3)
Research Program(s):
  1. 2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217) (POF4-217)
  2. BonaRes - (Modul A, Phase 2): Soil3-II - Nachhaltiges Unterbodenmanagement, Teilprojekt C (031B0515C) (031B0515C)
  3. BonaRes (Modul A): Nachhaltiges Unterbodenmanagement - Soil³, Teilprojekt 3 (031B0026C) (031B0026C)
  4. DFG project G:(GEPRIS)390732324 - EXC 2070 PhenoRob2 - Robotik und Phänotypisierung für Nachhaltige Nutzpflanzenproduktion (390732324) (390732324)
  5. EXC 2070:  PhenoRob - Robotics and Phenotyping for Sustainable Crop Production (390732324) (390732324)

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The record appears in these collections:
Institute Collections > IBG > IBG-3
Workflow collections > Relevant for Publication database
Workflow collections > User submitted records

 Record created 2026-10-14, last modified 2026-10-18



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