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Related Experiment Video

Updated: Mar 15, 2026

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

Technical Note: plastimatch mabs, an open source tool for automatic image segmentation.

Paolo Zaffino¹, Patrik Raudaschl², Karl Fritscher²

¹Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro 88100, Italy.

Medical Physics

|September 3, 2016

Summary

This summary is machine-generated.

This study introduces plastimatch mabs, an open-source software for multiatlas-based segmentation applicable to any image modality and anatomical region. It offers a flexible solution for both clinical and research applications, enabling efficient and accurate automatic segmentation.

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Last Updated: Mar 15, 2026

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Area of Science:

Medical Imaging
Computational Anatomy
Radiotherapy Planning
Neuroscience

Background:

Multi-atlas based segmentation (MABS) is widely used in clinical and research settings.
Current MABS software often has restrictions on anatomical regions and image modalities.
This limitation hinders broader application in diverse medical imaging tasks.

Purpose of the Study:

Introduce plastimatch mabs, an open-source software for unrestricted multi-atlas based segmentation.
Provide a versatile tool applicable to any image modality and anatomical district.
Address the need for a flexible MABS software in clinical and research environments.

Main Methods:

The plastimatch mabs workflow involves an offline phase for parameter tuning and an online phase for new patient segmentation.
It supports various registration strategies, voting criteria, and an atlas selection scheme.
Effectiveness was validated on head and neck CT and brain MRI datasets.

Main Results:

Achieved minimum Dice scores of 0.76 for brain structures and 0.42-0.62 for head and neck structures.
Segmentation times were compatible with clinical workflows (35-120 minutes).
Demonstrated effectiveness across different anatomical regions and imaging modalities.

Conclusions:

plastimatch mabs fills a critical gap by offering unrestricted multi-atlas based segmentation.
The software serves as a platform for exploring MABS parameters and algorithm comparison.
It provides a valuable, flexible tool for diverse medical imaging segmentation needs.