Article

Automated Pediatric Brain Tumor Imaging Assessment Tool from CBTN: Enhancing Suprasellar Region Inclusion and Managing Limited Data with Deep Learning

2024-07-31

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Fully-automatic skull-stripping and tumor segmentation are crucial for monitoring pediatric brain tumors (PBT). Current methods, however, often lack generalizability, particularly for rare tumors in the sellar/suprasellar regions and when applied to real-world clinical data in limited data scenarios. To address these challenges, we propose AI-driven techniques for skull-stripp...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: f8f502e7-9b2f-5932-bf5c-320e1581046b
DOI: 10.1101/2024.07.29.24311006

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Automated Pediatric Brain Tumor Imaging Assessment Tool from CBTN: Enhancing Suprasellar Region Inclusion and Managing Limited Data with Deep LearningDOI 10.1101/2024.07.29.24311006Read

Automated Tumor Segmentation and Brain Tissue Extraction from Multiparametric MRI of Pediatric Brain Tumors: A Multi-Institutional StudySemantic proximity Read

Expert-level pediatric brain tumor segmentation in a limited data scenario with stepwise transfer learningSemantic proximity Read

Automated Brain and CSF Volume Assessment in Infant Hydrocephalus Using Deep LearningSemantic proximity Read

AI-Powered Segmentation and Prognosis with Missing MRI in Pediatric Brain TumorsSemantic proximity Read

Advancing Precision: A Comprehensive Review of MRI Segmentation Datasets from BraTS Challenges (2012–2024)Semantic proximity Read

Noninvasive molecular subtyping of pediatric low-grade glioma with self-supervised transfer learningSemantic proximity Read

A multicenter Swedish histopathology image dataset of pediatric central nervous system tumorsSemantic proximity Read

A Generative Skull Stripping of Multiparametric Brain MRIs Using 3D Convolutional Neural NetworkSemantic proximity Read

Deep Learning for Automated Meningioma Segmentation: Toward Clinical Integration and Workflow EfficiencySemantic proximity Read

Automated Longitudinal MRI Assessments of Diffuse Midline Gliomas: A Large Multi-Institutional StudySemantic proximity Read

Deep Learning for Automatic Segmentation of Vestibular Schwannoma: A Retrospective Study from Multi-Centre Routine MRISemantic proximity Read

Brain tumor segmentation using a combination of graph cut and optimized U-Net with genetic algorithm: An efficient hybrid framework for enhanced medical image analysisSemantic proximity Read