Unified HT-CNNs Architecture: Transfer Learning for Segmenting Diverse Brain Tumors in MRI from Gliomas to Pediatric Tumors
RA Zeineldin, F Mathis-Ullrich - arXiv preprint arXiv:2412.08240, 2024 - arxiv.org
Accurate segmentation of brain tumors from 3D multimodal MRI is vital for diagnosis and
treatment planning across diverse brain tumors. This paper addresses the challenges posed …
treatment planning across diverse brain tumors. This paper addresses the challenges posed …
Automated pediatric brain tumor imaging assessment tool from CBTN: Enhancing suprasellar region inclusion and managing limited data with deep learning
Background Fully automatic skull-stripping and tumor segmentation are crucial for
monitoring pediatric brain tumors (PBT). Current methods, however, often lack …
monitoring pediatric brain tumors (PBT). Current methods, however, often lack …
Segmentation of Pediatric Brain Tumors using a Radiologically informed, Deep Learning Cascade
Monitoring of Diffuse Intrinsic Pontine Glioma (DIPG) and Diffuse Midline Glioma (DMG)
brain tumors in pediatric patients is key for assessment of treatment response. Response …
brain tumors in pediatric patients is key for assessment of treatment response. Response …
A New Logic For Pediatric Brain Tumor Segmentation
In this paper, we present a novel approach for segmenting pediatric brain tumors using a
deep learning architecture, inspired by expert radiologists' segmentation strategies. Our …
deep learning architecture, inspired by expert radiologists' segmentation strategies. Our …
3D Graph Attention Networks for High Fidelity Pediatric Glioma Segmentation
H Thangaraj, D Katariya, E Joshi - arXiv preprint arXiv:2412.06743, 2024 - arxiv.org
Pediatric brain tumors, particularly gliomas, represent a significant cause of cancer related
mortality in children with complex infiltrative growth patterns that complicate treatment. Early …
mortality in children with complex infiltrative growth patterns that complicate treatment. Early …