Deep learning for pediatric posterior fossa tumor detection and classification: a multi-institutional study
BACKGROUND AND PURPOSE: Posterior fossa tumors are the most common pediatric
brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We …
brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We …
Automatic machine learning to differentiate pediatric posterior fossa tumors on routine MR imaging
H Zhou, R Hu, O Tang, C Hu, L Tang… - American Journal …, 2020 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Differentiating the types of pediatric posterior fossa tumors
on routine imaging may help in preoperative evaluation and guide surgical resection …
on routine imaging may help in preoperative evaluation and guide surgical resection …
[HTML][HTML] Deep learning-based studies on pediatric brain tumors imaging: narrative review of techniques and challenges
Brain tumors diagnosis in children is a scientific concern due to rapid anatomical, metabolic,
and functional changes arising in the brain and non-specific or conflicting imaging results …
and functional changes arising in the brain and non-specific or conflicting imaging results …
MRI-based end-to-end pediatric low-grade glioma segmentation and classification
Purpose: MRI-based radiomics models can predict genetic markers in pediatric low-grade
glioma (pLGG). These models usually require tumour segmentation, which is tedious and …
glioma (pLGG). These models usually require tumour segmentation, which is tedious and …
Development and validation of a deep learning model for brain tumor diagnosis and classification using magnetic resonance imaging
P Gao, W Shan, Y Guo, Y Wang, R Sun, J Cai… - JAMA Network …, 2022 - jamanetwork.com
Importance Deep learning may be able to use patient magnetic resonance imaging (MRI)
data to aid in brain tumor classification and diagnosis. Objective To develop and clinically …
data to aid in brain tumor classification and diagnosis. Objective To develop and clinically …
[HTML][HTML] CoMB-deep: composite deep learning-based pipeline for classifying childhood medulloblastoma and its classes
O Attallah - Frontiers in neuroinformatics, 2021 - frontiersin.org
Childhood medulloblastoma (MB) is a threatening malignant tumor affecting children all over
the globe. It is the foremost common pediatric brain tumor causing death. The early and …
the globe. It is the foremost common pediatric brain tumor causing death. The early and …
Automated tumor segmentation and brain tissue extraction from multiparametric MRI of pediatric brain tumors: A multi-institutional study
A Fathi Kazerooni, S Arif, R Madhogarhia… - Neuro-Oncology …, 2023 - academic.oup.com
Background Brain tumors are the most common solid tumors and the leading cause of
cancer-related death among all childhood cancers. Tumor segmentation is essential in …
cancer-related death among all childhood cancers. Tumor segmentation is essential in …
Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors
J Peng, DD Kim, JB Patel, X Zeng, J Huang… - Neuro …, 2022 - academic.oup.com
Background Longitudinal measurement of tumor burden with magnetic resonance imaging
(MRI) is an essential component of response assessment in pediatric brain tumors. We …
(MRI) is an essential component of response assessment in pediatric brain tumors. We …
[HTML][HTML] TumorDetNet: A unified deep learning model for brain tumor detection and classification
Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment
process and helps to save the lives of a large number of people worldwide. Because they …
process and helps to save the lives of a large number of people worldwide. Because they …
Deep radiomics for brain tumor detection and classification from multi-sequence MRI
Glioma constitutes 80% of malignant primary brain tumors and is usually classified as HGG
and LGG. The LGG tumors are less aggressive, with slower growth rate as compared to …
and LGG. The LGG tumors are less aggressive, with slower growth rate as compared to …