Brain Cancer

Predicting the outcome of radiotherapy in brain metastasis by integrating the clinical and MRI-based deep learning features.

BACKGROUND: A considerable proportion of metastatic brain tumors progress locally despite stereotact...

Fast intraoperative histology-based diagnosis of gliomas with third harmonic generation microscopy and deep learning.

Management of gliomas requires an invasive treatment strategy, including extensive surgical resectio...

Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.

BACKGROUND: Accurate and rapid measurement of the MRI volume of meningiomas is essential in clinical...

Editorial for "Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning".

Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach.

Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important ...

A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method.

Raman spectroscopy is a spectroscopic technique typically used to determine vibrational modes of mol...

A state-of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture.

Glioma is the most aggressive and dangerous primary brain tumor with a survival time of less than 14...

Eliminating CT radiation for clinical PET examination using deep learning.

Clinical PET/CT examinations rely on CT modality for anatomical localization and attenuation correct...

Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images.

Despite the progress made during the last two decades in the surgery and chemotherapy of ovarian can...

Deep learning based analysis of microstructured materials for thermal radiation control.

Microstructured materials that can selectively control the optical properties are crucial for the de...

Liver Attenuation Assessment in Reduced Radiation Chest Computed Tomography.

OBJECTIVE: This study aimed to evaluate the reliability of liver and spleen Hounsfield units (HU) me...

A deep learning-based radiomics approach to predict head and neck tumor regression for adaptive radiotherapy.

Early regression-the regression in tumor volume during the initial phase of radiotherapy (approximat...

Design of Nuclear Radiation Monitoring System in Floor Exploration Based on Deep Learning.

Nuclear radiation environmental monitoring has become an important issue in floor surveys. From the ...

AI-based optimization for US-guided radiation therapy of the prostate.

OBJECTIVES: Fast volumetric ultrasound presents an interesting modality for continuous and real-time...

End-to-end deep learning for interior tomography with low-dose x-ray CT.

There are several x-ray computed tomography (CT) scanning strategies used to reduce radiation dose, ...

Reversing radiation-induced immunosuppression using a new therapeutic modality.

Radiation-induced immune suppression poses significant health challenges for millions of patients un...

MRCON-Net: Multiscale reweighted convolutional coding neural network for low-dose CT imaging.

BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) has become increasingly important for ...

Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma-a systematic review.

OBJECTIVES: Radiomics is a promising avenue in non-invasive characterisation of diffuse glioma. Clin...

Computed Tomography Images under Artificial Intelligence Algorithms on the Treatment Evaluation of Intracerebral Hemorrhage with Minimally Invasive Aspiration.

The aim of this study was to investigate the therapeutic effect of minimally invasive aspiration on ...

Automatic hemorrhage segmentation on head CT scan for traumatic brain injury using 3D deep learning model.

The most common cause of long-term disability and death in young adults is a traumatic brain injury....

Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.

OBJECTIVES: Develop and evaluate a deep learning-based automatic meningioma segmentation method for ...