Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases
A recent meeting was held on March 22, 2019, among the FDA, clinical scientists,
pharmaceutical and biotech companies, clinical trials cooperative groups, and patient …
pharmaceutical and biotech companies, clinical trials cooperative groups, and patient …
Brain metastases: A Society for Neuro-Oncology (SNO) consensus review on current management and future directions
AA Aizer, N Lamba, MS Ahluwalia, K Aldape… - Neuro …, 2022 - academic.oup.com
Brain metastases occur commonly in patients with advanced solid malignancies. Yet, less is
known about brain metastases than cancer-related entities of similar incidence. Advances in …
known about brain metastases than cancer-related entities of similar incidence. Advances in …
Robust performance of deep learning for automatic detection and segmentation of brain metastases using three-dimensional black-blood and three-dimensional …
Objectives To evaluate whether a deep learning (DL) model using both three-dimensional
(3D) black-blood (BB) imaging and 3D gradient echo (GRE) imaging may improve the …
(3D) black-blood (BB) imaging and 3D gradient echo (GRE) imaging may improve the …
Brain tumor-enhancement visualization and morphometric assessment: a comparison of MPRAGE, SPACE, and VIBE MRI techniques
L Danieli, GC Riccitelli, D Distefano… - American Journal …, 2019 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Postgadolinium MR imaging is crucial for brain tumor
diagnosis and morphometric assessment. We compared brain tumor enhancement …
diagnosis and morphometric assessment. We compared brain tumor enhancement …
A historical overview of magnetic resonance imaging, focusing on technological innovations
T Ai, JN Morelli, X Hu, D Hao, FL Goerner… - Investigative …, 2012 - journals.lww.com
Magnetic resonance imaging (MRI) has now been used clinically for more than 30 years.
Today, MRI serves as the primary diagnostic modality for many clinical problems. In this …
Today, MRI serves as the primary diagnostic modality for many clinical problems. In this …
Recent advances in MRI of the head and neck, skull base and cranial nerves: new and evolving sequences, analyses and clinical applications
P Touska, SEJ Connor - The British Journal of Radiology, 2019 - academic.oup.com
MRI is an invaluable diagnostic tool in the investigation and management of patients with
pathology of the head and neck. However, numerous technical challenges exist, owing to a …
pathology of the head and neck. However, numerous technical challenges exist, owing to a …
Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors
Black-blood (BB) imaging is used to complement contrast-enhanced 3D gradient-echo (CE
3D-GRE) imaging for detecting brain metastases, requiring additional scan time. In this …
3D-GRE) imaging for detecting brain metastases, requiring additional scan time. In this …
MR-self Noise2Noise: self-supervised deep learning–based image quality improvement of submillimeter resolution 3D MR images
Objectives The study aimed to develop a deep neural network (DNN)–based noise
reduction and image quality improvement by only using routine clinical scans and evaluate …
reduction and image quality improvement by only using routine clinical scans and evaluate …
Post-contrast 3D T1-weighted TSE MR sequences (SPACE, CUBE, VISTA/BRAINVIEW, isoFSE, 3D MVOX): Technical aspects and clinical applications
B Bapst, JL Amegnizin, A Vignaud, P Kauv… - Journal of …, 2020 - Elsevier
Post-contrast three-dimensional T1-weighted imaging of the brain is widely used for a broad
range of vascular, inflammatory or tumoral diseases. The variable flip angle 3D TSE …
range of vascular, inflammatory or tumoral diseases. The variable flip angle 3D TSE …
A deep convolutional neural network-based automatic detection of brain metastases with and without blood vessel suppression
Y Kikuchi, O Togao, K Kikuchi, D Momosaka… - European …, 2022 - Springer
Objectives To develop an automated model to detect brain metastases using a convolutional
neural network (CNN) and volume isotropic simultaneous interleaved bright-blood and black …
neural network (CNN) and volume isotropic simultaneous interleaved bright-blood and black …
