Slicer-DeepSeg: Open-Source Deep Learning Toolkit for Brain Tumour Segmentation

Zeineldin RA, Weimann P, Karar ME, Mathis-Ullrich F, Burgert O (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Current Directions in Biomedical Engineering De Gruyter

Book Volume: 7

Article Number: 20211107

Journal Issue: 1

DOI: 10.1515/cdbme-2021-1007

Abstract

Purpose Computerized medical imaging processing assists neurosurgeons to localize tumours precisely. It plays a key role in recent image-guided neurosurgery. Hence, we developed a new open-source toolkit, namely Slicer-DeepSeg, for efficient and automatic brain tumour segmentation based on deep learning methodologies for aiding clinical brain research. Methods Our developed toolkit consists of three main components. First, Slicer-DeepSeg extends the 3D Slicer application and thus provides support for multiple data input/output data formats and 3D visualization libraries. Second, Slicer core modules offer powerful image processing and analysis utilities. Third, the Slicer-DeepSeg extension provides a customized GUI for brain tumour segmentation using deep learning-based methods. Results The developed Slicer-DeepSeg was validated using a public dataset of high-grade glioma patients. The results showed that our proposed platform's performance considerably outperforms other 3D Slicer cloud-based approaches. Conclusions Developed Slicer-DeepSeg allows the development of novel AIassisted medical applications in neurosurgery. Moreover, it can enhance the outcomes of computer-aided diagnosis of brain tumours. Open-source Slicer-DeepSeg is available at github.com/razeineldin/Slicer-DeepSeg.

Authors with CRIS profile

Franziska Mathis-Ullrich

Involved external institutions

Karlsruhe Institute of Technology (KIT) DE Germany (DE) Hochschule Reutlingen DE Germany (DE)

How to cite

APA:

Zeineldin, R.A., Weimann, P., Karar, M.E., Mathis-Ullrich, F., & Burgert, O. (2021). Slicer-DeepSeg: Open-Source Deep Learning Toolkit for Brain Tumour Segmentation. Current Directions in Biomedical Engineering, 7(1). https://doi.org/10.1515/cdbme-2021-1007

MLA:

Zeineldin, Ramy A., et al. "Slicer-DeepSeg: Open-Source Deep Learning Toolkit for Brain Tumour Segmentation." Current Directions in Biomedical Engineering 7.1 (2021).

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