Oncology/Hematology

Brain Cancer

Latest AI and machine learning research in brain cancer for healthcare professionals.

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Artificial intelligence in image reconstruction: The change is here.

Innovations in CT have been impressive among imaging and medical technologies in both the hardware a...

Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learning.

Differentiating pseudoprogression from true tumor progression has become a significant challenge in ...

Improving Image Quality and Reducing Radiation Dose for Pediatric CT by Using Deep Learning Reconstruction.

Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image nois...

Dose-dependent effects of ultrasound therapy on hepatocellular carcinoma.

Non-invasive ischemic cancer therapy requires reduced blood flow whereas drug delivery and radiation...

Using Auto-Segmentation to Reduce Contouring and Dose Inconsistency in Clinical Trials: The Simulated Impact on RTOG 0617.

PURPOSE: Contouring inconsistencies are known but understudied in clinical radiation therapy trials....

Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy.

Complete resection of the tumor is important for survival in glioma patients. Even if the gross tota...

Automatic Segmentation Using Deep Learning to Enable Online Dose Optimization During Adaptive Radiation Therapy of Cervical Cancer.

PURPOSE: This study investigated deep learning models for automatic segmentation to support the deve...

Obtaining PET/CT images from non-attenuation corrected PET images in a single PET system using Wasserstein generative adversarial networks.

Positron emission tomography (PET) imaging plays an indispensable role in early disease detection an...

Dose prediction with deep learning for prostate cancer radiation therapy: Model adaptation to different treatment planning practices.

PURPOSE: This work aims to study the generalizability of a pre-developed deep learning (DL) dose pre...

Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI.

Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-re...

The Coming of Age for Big Data in Systems Radiobiology, an Engineering Perspective.

As high-throughput approaches in biological and biomedical research are transforming the life scienc...

Integration of AI and Machine Learning in Radiotherapy QA.

The use of machine learning and other sophisticated models to aid in prediction and decision making ...

Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer.

Manual segmentation is the gold standard method for radiation therapy planning; however, it is time-...

Deep Learning Model for the Automated Detection and Histopathological Prediction of Meningioma.

The volumetric assessment and accurate grading of meningiomas before surgery are highly relevant for...

Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy.

This brief review summarizes the major applications of artificial intelligence (AI), in particular d...

Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis.

Methylation of the O-methylguanine methyltransferase (MGMT) gene promoter is correlated with the eff...

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