Brain Cancer

Radiomics and deep learning in lung cancer.

Lung malignancies have been extensively characterized through radiomics and deep learning. By provid...

Artificial intelligence in glioma imaging: challenges and advances.

Primary brain tumors including gliomas continue to pose significant management challenges to clinici...

Fully automatic brain tumor segmentation with deep learning-based selective attention using overlapping patches and multi-class weighted cross-entropy.

In this paper, we present a new Deep Convolutional Neural Networks (CNNs) dedicated to fully automat...

High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study.

Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting...

Ependymoma and pilocytic astrocytoma: Differentiation using radiomics approach based on machine learning.

Mandatory accurate and specific diagnosis demands have brought about increased challenges for radiol...

Brain tumor segmentation and grading of lower-grade glioma using deep learning in MRI images.

Gliomas are the most common malignant brain tumors with different grades that highly determine the r...

Brain tumor classification of virtual NMR voxels based on realistic blood vessel-induced spin dephasing using support vector machines.

Remodeling of tissue microvasculature commonly promotes neoplastic growth; however, there is no imag...

A Surrogate Model Based on Artificial Neural Network for RF Radiation Modelling with High-Dimensional Data.

This paper focuses on quantifying the uncertainty in the specific absorption rate valuesof the brain...

DeepDose: Towards a fast dose calculation engine for radiation therapy using deep learning.

We present DeepDose, a deep learning framework for fast dose calculations in radiation therapy. Give...

Precise pulmonary scanning and reducing medical radiation exposure by developing a clinically applicable intelligent CT system: Toward improving patient care.

BACKGROUND: Interstitial lung disease requires frequent re-examination, which directly causes excess...

PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers.

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, art...

Re: Comparison of Outcomes of Salvage Robot-Assisted Laparoscopic Prostatectomy for Post-Primary Radiation vs Focal Therapy.

Deep learning-based radiomic features for improving neoadjuvant chemoradiation response prediction in locally advanced rectal cancer.

Radiomic features achieve promising results in cancer diagnosis, treatment response prediction, and ...

Ontologies in radiation oncology.

Ontologies are a formal, computer-compatible method for representing scientific knowledge about a gi...

Brain tumor classification using modified local binary patterns (LBP) feature extraction methods.

Automatic classification of brain tumor types is very important for accelerating the treatment proce...

Improved Prediction of Surgical Resectability in Patients with Glioblastoma using an Artificial Neural Network.

In managing a patient with glioblastoma (GBM), a surgeon must carefully consider whether sufficient ...

Diagnostic accuracy and potential covariates for machine learning to identify IDH mutations in glioma patients: evidence from a meta-analysis.

OBJECTIVES: To assess the diagnostic accuracy of machine learning (ML) in predicting isocitrate dehy...

Computer-aided Detection of Brain Metastases in T1-weighted MRI for Stereotactic Radiosurgery Using Deep Learning Single-Shot Detectors.

Background Brain metastases are manually identified during stereotactic radiosurgery (SRS) treatment...

Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma.

BACKGROUND: Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonl...

Artificial intelligence as the next step towards precision pathology.

Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of c...

The Impact of Artificial Intelligence and Machine Learning in Radiation Therapy: Considerations for Future Curriculum Enhancement.

Artificial intelligence (AI) and machine learning (ML) approaches have caught the attention of many ...