MRI based medical image analysis: Survey on brain tumor grade classification
G Mohan, MM Subashini - Biomedical Signal Processing and Control, 2018 - Elsevier
A review on the recent segmentation and tumor grade classification techniques of brain
Magnetic Resonance (MR) Images is the objective of this paper. The requisite for early …
Magnetic Resonance (MR) Images is the objective of this paper. The requisite for early …
[HTML][HTML] Optimizing neuro-oncology imaging: a review of deep learning approaches for glioma imaging
MM Shaver, PA Kohanteb, C Chiou, MD Bardis… - Cancers, 2019 - mdpi.com
Radiographic assessment with magnetic resonance imaging (MRI) is widely used to
characterize gliomas, which represent 80% of all primary malignant brain tumors …
characterize gliomas, which represent 80% of all primary malignant brain tumors …
Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study
P Kickingereder, F Isensee, I Tursunova… - The Lancet …, 2019 - thelancet.com
Summary Background The Response Assessment in Neuro-Oncology (RANO) criteria and
requirements for a uniform protocol have been introduced to standardise assessment of MRI …
requirements for a uniform protocol have been introduced to standardise assessment of MRI …
Identification of non–small cell lung cancer sensitive to systemic cancer therapies using radiomics
Purpose: Using standard-of-care CT images obtained from patients with a diagnosis of non–
small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of …
small cell lung cancer (NSCLC), we defined radiomics signatures predicting the sensitivity of …
A survey on brain tumor detection techniques for MR images
PK Chahal, S Pandey, S Goel - Multimedia Tools and Applications, 2020 - Springer
One of the most crucial tasks in any brain tumor detection system is the isolation of abnormal
tissues from normal brain tissues. Interestingly, domain of brain tumor analysis has …
tissues from normal brain tissues. Interestingly, domain of brain tumor analysis has …
Aggressive resection at the infiltrative margins of glioblastoma facilitated by intraoperative fluorescein guidance
JA Neira, TH Ung, JS Sims, HR Malone… - Journal of …, 2016 - thejns.org
OBJECTIVE Extent of resection is an important prognostic factor in patients undergoing
surgery for glioblastoma (GBM). Recent evidence suggests that intravenously administered …
surgery for glioblastoma (GBM). Recent evidence suggests that intravenously administered …
Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab
Background Bevacizumab is a humanized antibody against vascular endothelial growth
factor approved for treatment of recurrent glioblastoma. There is a need to discover imaging …
factor approved for treatment of recurrent glioblastoma. There is a need to discover imaging …
Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre-and post-operative glioblastoma patients
Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation
of treatment response for glioblastoma. This assessment is, however, complex to perform …
of treatment response for glioblastoma. This assessment is, however, complex to perform …
A deep learning model for discriminating true progression from pseudoprogression in glioblastoma patients
Abstract Introduction Glioblastomas (GBMs) are highly aggressive tumors. A common
clinical challenge after standard of care treatment is differentiating tumor progression from …
clinical challenge after standard of care treatment is differentiating tumor progression from …
A data constrained approach for brain tumour detection using fused deep features and SVM
The identification of MR images of the brain with tumours is one of the most critical tasks of
any brain tumour (BT) detection system. Interestingly, because of its non-invasive image …
any brain tumour (BT) detection system. Interestingly, because of its non-invasive image …
