ArticleScientific reports2023
Raidionics: an open software for pre- and postoperative central nervous system tumor segmentation and standardized reporting.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Article
- Neurosurgical Application of Artificial Intelligence in Pediatric Neuro-Oncology.Journal of Korean Neurosurgical Society · 2026Article
- Assessing Impact of Data Quality in Early Post-Operative Glioblastoma Segmentation.Journal of imaging · 2026Article
- Prediction of MGMT promoter methylation in glioblastoma and grade 4 astrocytoma using fluid-suppressed chemical exchange saturation transfer MRI and machine learning-based segmentation.Frontiers in oncology · 2026Article
- Novel predictors of tumor growth by exploratory quantitative analysis of radiomics features from MRI data for incidentally discovered meningioma.Journal of neuro-oncology · 2025Article
- Automatic Brain Tumor Segmentation in 2D Intra-Operative Ultrasound Images Using Magnetic Resonance Imaging Tumor Annotations.Journal of imaging · 2025Article
- Clinical evaluation of two glioblastoma delineation methods based on neural networks.Technical innovations & patient support in radiation oncology · 2025Article
- Survival prediction with radiomics for patients with IDH mutated lower-grade glioma.Journal of neuro-oncology · 2025Article
- Factors contributing to variability in neurocognitive performance before glioma neurosurgery.Neuro-oncology practice · 2025Article
- Noninvasive MGMT-promotor methylation prediction in high grade gliomas using conventional MRI and deep learning-based segmentations.Frontiers in neuroscience · 2025Article
- Automatic and standardized reporting of perioperative MRIs in patients with central nervous system tumors.Frontiers in neurology · 2025Article
- Assessing glymphatic dysfunction using the diffusion tensor image analysis along the perivascular space (DTI-ALPS) index in gliomas and metastases.Polish journal of radiology · 2025Article
- Transfer Learning Approaches for Brain Metastases Screenings.Biomedicines · 2024Article
- RhizoNet segments plant roots to assess biomass and growth for enabling self-driving labs.Scientific reports · 2024Article
- AeroPath: An airway segmentation benchmark dataset with challenging pathology and baseline method.PloS one · 2024Article
- Estimating overall survival of glioblastoma patients using clinical variables, tumor size, and location.Neuro-oncology advancesArticle
- Validation of open-source deep learning segmentation tools for automated glioma volumetry: a narrative review of Dice scores, workflow efficiency, and clinical RANO 2.0 implementation.Frontiers in neurologyReview
- Deep learning-based postoperative glioblastoma segmentation and extent of resection evaluation: Development, external validation, and model comparison.Neuro-oncology advancesArticle
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7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
For patients suffering from central nervous system tumors, prognosis estimation, treatment decisions, and postoperative assessments are made from the analysis of a set of magnetic resonance (MR) scans. Currently, the lack of open tools for standardized and automatic tumor segmentation and generation of clinical reports, incorporating relevant tumor characteristics, leads to potential risks from inherent decisions' subjectivity. To tackle this problem, the proposed Raidionics open-source software has been developed, offering both a user-friendly graphical user interface and stable processing backend. The software includes preoperative segmentation models for each of the most common tumor types (i.e., glioblastomas, lower grade gliomas, meningiomas, and metastases), together with one early postoperative glioblastoma segmentation model. Preoperative segmentation performances were quite homogeneous across the four different brain tumor types, with an average Dice around 85% and patient-wise recall and precision around 95%. Postoperatively, performances were lower with an average Dice of 41%. Overall, the generation of a standardized clinical report, including the tumor segmentation and features computation, requires about ten minutes on a regular laptop. The proposed Raidionics software is the first open solution enabling an easy use of state-of-the-art segmentation models for all major tumor types, including preoperative and postsurgical standardized reports.
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