Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features
Gliomas belong to a group of central nervous system tumors, and consist of various sub-
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment,
and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from …
and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from …
Automatic brain lesion segmentation on standard magnetic resonance images: a scoping review
Objectives Medical image analysis practices face challenges that can potentially be
addressed with algorithm-based segmentation tools. In this study, we map the field of …
addressed with algorithm-based segmentation tools. In this study, we map the field of …
AI and high-grade glioma for diagnosis and outcome prediction: do all machine learning models perform equally well?
L Pasquini, A Napolitano, M Lucignani… - Frontiers in …, 2021 - frontiersin.org
Radiomic models outperform clinical data for outcome prediction in high-grade gliomas
(HGG). However, lack of parameter standardization limits clinical applications. Many …
(HGG). However, lack of parameter standardization limits clinical applications. Many …
An end‐to‐end brain tumor segmentation system using multi‐inception‐UNET
Accurate detection and pixel‐wise classification of brain tumors in Magnetic Resonance
Imaging (MRI) scans are vital for their diagnosis, prognosis study and treatment planning …
Imaging (MRI) scans are vital for their diagnosis, prognosis study and treatment planning …
U-net supported segmentation of ischemic-stroke-lesion from brain MRI slices
The brain abnormality is one of the major sicknesses in human's health and the untreated
brain defect will cause major illness. Ischemic stroke is one of the major medical …
brain defect will cause major illness. Ischemic stroke is one of the major medical …
Cascaded V-Net using ROI masks for brain tumor segmentation
In this work we approach the brain tumor segmentation problem with a cascade of two CNNs
inspired in the V-Net architecture [13], reformulating residual connections and making use of …
inspired in the V-Net architecture [13], reformulating residual connections and making use of …
Automated segmentation of hyperintense regions in FLAIR MRI using deep learning
We present a deep convolutional neural network application based on autoencoders aimed
at segmentation of increased signal regions in fluid-attenuated inversion recovery magnetic …
at segmentation of increased signal regions in fluid-attenuated inversion recovery magnetic …
3D convolutional neural networks for brain tumor segmentation: A comparison of multi-resolution architectures
A Casamitjana, S Puch, A Aduriz… - International Workshop on …, 2016 - Springer
This paper analyzes the use of 3D Convolutional Neural Networks for brain tumor
segmentation in MR images. We address the problem using three different architectures that …
segmentation in MR images. We address the problem using three different architectures that …
Automated detection of brain abnormality using deep-learning-scheme: a study
Brain is the vital organ in human physiology; which is conscientious for sensory signal
handling and judgment making. The irregularity in brain severely influence entire decision …
handling and judgment making. The irregularity in brain severely influence entire decision …