The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 1—Key Points of the Fifth Edition and Summary of Imaging Findings on Adult …
The fifth edition of the World Health Organization (WHO) classification of central nervous
system tumors published in 2021 advances the role of molecular diagnostics in the …
system tumors published in 2021 advances the role of molecular diagnostics in the …
Review and consensus recommendations on clinical APT‐weighted imaging approaches at 3T: application to brain tumors
Amide proton transfer‐weighted (APTw) MR imaging shows promise as a biomarker of brain
tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially …
tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially …
[HTML][HTML] Federated learning enables big data for rare cancer boundary detection
Although machine learning (ML) has shown promise across disciplines, out-of-sample
generalizability is concerning. This is currently addressed by sharing multi-site data, but such …
generalizability is concerning. This is currently addressed by sharing multi-site data, but such …
Added value of gadoxetic acid–enhanced hepatobiliary phase MR imaging in the diagnosis of hepatocellular carcinoma
Purpose To determine the added value of hepatobiliary phase images in gadoxetic acid–enhanced
magnetic resonance (MR) imaging in the evaluation of hepatocellular carcinoma (…
magnetic resonance (MR) imaging in the evaluation of hepatocellular carcinoma (…
The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 2—Summary of Imaging Findings on Pediatric‐Type Diffuse High‐Grade …
The fifth edition of the World Health Organization (WHO) classification of central nervous
system tumors published in 2021 advances the role of molecular diagnostics in the …
system tumors published in 2021 advances the role of molecular diagnostics in the …
Variational information distillation for knowledge transfer
Transferring knowledge from a teacher neural network pretrained on the same or a similar
task to a student neural network can significantly improve the performance of the student …
task to a student neural network can significantly improve the performance of the student …
Radiomic MRI phenotyping of glioblastoma: improving survival prediction
Purpose To investigate whether radiomic features at MRI improve survival prediction in
patients with glioblastoma multiforme (GBM) when they are integrated with clinical and genetic …
patients with glioblastoma multiforme (GBM) when they are integrated with clinical and genetic …
Learning from failure: De-biasing classifier from biased classifier
Neural networks often learn to make predictions that overly rely on spurious corre-lation
existing in the dataset, which causes the model to be biased. While previous work tackles this …
existing in the dataset, which causes the model to be biased. While previous work tackles this …
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging
Objectives Preoperative, noninvasive prediction of the meningioma grade is important because
it influences the treatment strategy. The purpose of this study was to evaluate the role of …
it influences the treatment strategy. The purpose of this study was to evaluate the role of …
Primary central nervous system lymphoma and atypical glioblastoma: differentiation using radiomics approach
Objectives To evaluate the diagnostic performance of magnetic resonance (MR) radiomics-based
machine-learning algorithms in differentiating primary central nervous system …
machine-learning algorithms in differentiating primary central nervous system …