Brain Cancer

Reducing radiation dose in routine CT scans: an AI-driven approach with deep learning-based dual-energy CT reconstruction.

Suitability of DNN-based vessel segmentation for SIRT planning.

PURPOSE: The segmentation of the hepatic arteries (HA) is essential for state-of-the-art pre-interve...

Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data.

OBJECTIVES: Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic im...

Submillimeter Multifunctional Ferromagnetic Fiber Robots for Navigation, Sensing, and Modulation.

Small-scale robots capable of remote active steering and navigation offer great potential for biomed...

Ultra-low-dose computed tomography with deep learning reconstruction for craniosynostosis at radiation doses comparable to skull radiographs: a pilot study.

BACKGROUND: Craniofacial computed tomography (CT) is the diagnostic investigation of choice for cran...

An AI Predictive Model to Determine Who Benefits from ADT with Radiation: Working Smarter, Not Harder.

Whether you are a surgical, medical, or radiation oncologist, the care goals remain the same, that i...

A deep-learning assisted bioluminescence tomography method to enable radiation targeting in rat glioblastoma.

. A novel solution is required for accurate 3D bioluminescence tomography (BLT) based glioblastoma (...

Auto-Segmentation and Classification of Glioma Tumors with the Goals of Treatment Response Assessment Using Deep Learning Based on Magnetic Resonance Imaging.

Glioma is the most common primary intracranial neoplasm in adults. Radiotherapy is a treatment appro...

Response to "Large language model artificial intelligence: the current state and future of ChatGPT in neuro-oncology publishing".

Machine learning to predict environmental dose rates from a radionuclide therapy service - a proof of concept study.

The Ionising Radiation Regulations 2017 requires prior risk assessment calculations and regular envi...

Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer.

PURPOSE: With the increased use of focal radiation dose escalation for primary prostate cancer (PCa)...

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized...

Deep learning-based body weight from scout images can be an alternative to actual body weight in CT radiation dose management.

PURPOSE: Accurate body weight measurement is essential to promote computed tomography (CT) dose opti...

Automated deep learning auto-segmentation of air volumes for MRI-guided online adaptive radiation therapy of abdominal tumors.

. In the current MR-Linac online adaptive workflow, air regions on the MR images need to be manually...

Editorial for "Preoperative Discrimination of CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytoma: A Deep Learning-Based Radiomics Model Using MRI".

Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma.

Determining the optimal course of treatment for low grade glioma (LGG) patients is challenging and f...

Artificial intelligence applications in prostate cancer.

Artificial intelligence (AI) applications have enabled remarkable advancements in healthcare deliver...

Deep-learning based fast and accurate 3D CT deformable image registration in lung cancer.

BACKGROUND: Deformable Image Registration (DIR) is an essential technique required in many applicati...

Is There a Role for Machine Learning in Liquid Biopsy for Brain Tumors? A Systematic Review.

The paucity of studies available in the literature on brain tumors demonstrates that liquid biopsy (...

Noise reduction performance of a deep learning-based reconstruction in brain computed tomography images acquired with organ-based tube current modulation.

We aimed to evaluate the image quality of brain computed tomography (CT) images reconstructed using ...

Predicting FDG-PET Images From Multi-Contrast MRI Using Deep Learning in Patients With Brain Neoplasms.

BACKGROUND: F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is valuable for determini...