Glioblastoma in adults: a Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future …

PY Wen, M Weller, EQ Lee, BM Alexander… - Neuro …, 2020 - academic.oup.com
Glioblastomas are the most common form of malignant primary brain tumor and an important
cause of morbidity and mortality. In recent years there have been important advances in …

[HTML][HTML] Evidence-based recommendations on categories for extent of resection in diffuse glioma

P Karschnia, MA Vogelbaum, M van den Bent… - European Journal of …, 2021 - Elsevier
Surgical resection represents the standard of care in diffuse glioma, and more extensive
tumour resection appears to be associated with favourable outcome. Up to now, terminology …

RANO 2.0: update to the response assessment in neuro-oncology criteria for high-and low-grade gliomas in adults

PY Wen, M Van Den Bent, G Youssef… - Journal of Clinical …, 2023 - ascopubs.org
PURPOSE The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade
gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve …

Assessing the trustworthiness of saliency maps for localizing abnormalities in medical imaging

N Arun, N Gaw, P Singh, K Chang… - Radiology: Artificial …, 2021 - pubs.rsna.org
Purpose To evaluate the trustworthiness of saliency maps for abnormality localization in
medical imaging. Materials and Methods Using two large publicly available radiology …

A survey on U-shaped networks in medical image segmentations

L Liu, J Cheng, Q Quan, FX Wu, YP Wang, J Wang - Neurocomputing, 2020 - Elsevier
The U-shaped network is one of the end-to-end convolutional neural networks (CNNs). In
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …

Emerging role of artificial intelligence in diagnosis, classification and clinical management of glioma

J Luo, M Pan, K Mo, Y Mao, D Zou - Seminars in cancer biology, 2023 - Elsevier
Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

A comprehensive survey on brain tumor diagnosis using deep learning and emerging hybrid techniques with multi-modal MR image

S Ali, J Li, Y Pei, R Khurram, KU Rehman… - … methods in engineering, 2022 - Springer
The brain tumor is considered the deadly disease of the century. At present, neuroscience
and artificial intelligence conspire in the timely delineation, detection, and classification of …

Portable, low-field magnetic resonance imaging enables highly accessible and dynamic bedside evaluation of ischemic stroke

MM Yuen, AM Prabhat, MH Mazurek, IR Chavva… - Science …, 2022 - science.org
Brain imaging is essential to the clinical management of patients with ischemic stroke.
Timely and accessible neuroimaging, however, can be limited in clinical stroke pathways …

Generative adversarial networks to synthesize missing T1 and FLAIR MRI sequences for use in a multisequence brain tumor segmentation model

GM Conte, AD Weston, DC Vogelsang, KA Philbrick… - Radiology, 2021 - pubs.rsna.org
Background Missing MRI sequences represent an obstacle in the development and use of
deep learning (DL) models that require multiple inputs. Purpose To determine if synthesizing …

[HTML][HTML] A customized VGG19 network with concatenation of deep and handcrafted features for brain tumor detection

V Ra**ikanth, AN Joseph Raj, KP Thanaraj, GR Naik - Applied Sciences, 2020 - mdpi.com
Brain tumor (BT) is one of the brain abnormalities which arises due to various reasons. The
unrecognized and untreated BT will increase the morbidity and mortality rates. The clinical …