Brain Cancer

Ultra-Sparse-View Cone-Beam CT Reconstruction-Based Strictly Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy.

Radiation therapy is regarded as the mainstay treatment for cancer in clinic. Kilovoltage cone-beam CT (CBCT) images have been acquired for most treatment sites as the clinical routine for image-guided radiation therapy (IGRT). However, repeated CBCT scanning brings extra irradiation dose to the patients and decreases clinical efficiency. Sparse CBCT scanning is a possible solution to the problems...

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting to Pediatric Emergency Departments (EDs). These fractures are treated conservatively or surgically depending on deformity severity. Radiographs are typically used for diagnosis but can increase wait times due to the need for radiation-safe rooms. Ultrasound (US) offers a radiation-free, faster alte...

Deep learning-based triple-tracer brain PET scanning in a single session: A simulation study using clinical data.

OBJECTIVES: Multiplexed Positron Emission Tomography (PET) imaging allows simultaneous acquisition of multiple radiotracer signals, thus enhancing dia...

Real-time brain tumour diagnoses using a novel lightweight deep learning model.

Brain tumours continue to be a primary cause of worldwide death, highlighting the critical need for effective and accurate diagnostic tools. This arti...

Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI.

Brain Tumours are highly complex, particularly when it comes to their initial and accurate diagnosis, as this determines patient prognosis. Convention...

Dimensional Synthesis of 6-DOF Parallel Robot for Intra-Operative Radiation Therapy.

BACKGROUND: In order to meet the kinematic requirements of large range of motion, payload, and stiffness of Intra-Operative Radiation Therapy robots, ...

Multi-class brain malignant tumor diagnosis in magnetic resonance imaging using convolutional neural networks.

Glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and brain metastases (BM) are common malignant brain tumors with similar radiolog...

Prediction methodology of air absorbed dose rates for Chinese cities with deep learning models.

Air absorbed dose rate is a key indicator of environmental radiation exposure. In China, automated environmental radiation monitoring systems have bee...

Driving Knowledge to Action: Building a Better Future With Artificial Intelligence-Enabled Multidisciplinary Oncology.

Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, redefining how clinicians detect, classify, and trea...

Efficient 3D Brain Tumor Segmentation with Axial-Coronal-Sagittal Embedding

In this paper, we address the crucial task of brain tumor segmentation in medical imaging and propose innovative approaches to enhance its performan...

Deep learning-driven modality imputation and subregion segmentation to enhance high-grade glioma grading.

PURPOSE: This study aims to develop a deep learning framework that leverages modality imputation and subregion segmentation to improve grading accurac...

Harnessing artificial intelligence to address immune response heterogeneity in low-dose radiation therapy.

Low-dose radiation therapy has emerged as a promising modality for cancer treatment because of its ability to stimulate antitumor immune responses whi...

Robotic radiation shielding system reduces radiation-induced DNA damage in operators performing electrophysiological procedures.

Fluoroscopically guided electrophysiology (EP) procedures expose operators to low doses of ionizing radiation, which can induce DNA double-strand brea...

Machine learning-driven imaging data for early prediction of lung toxicity in breast cancer radiotherapy.

One possible adverse effect of breast irradiation is the development of pulmonary fibrosis. The aim of this study was to determine whether planning CT...

Machine learning decision support model construction for craniotomy approach of pineal region tumors based on MRI images.

BACKGROUND: Pineal region tumors (PRTs) are rare but deep-seated brain tumors, and complete surgical resection is crucial for effective tumor treatmen...

Federated prediction for scalable and privacy-preserved knowledge-based planning in radiotherapy

Background: Deep learning has potential to improve the efficiency and consistency of radiation therapy planning, but clinical adoption is hindered b...

A generalisable head MRI defacing pipeline: Evaluation on 2,566 meningioma scans

Reliable MRI defacing techniques to safeguard patient privacy while preserving brain anatomy are critical for research collaboration. Existing metho...

Reconstruction of partially obscured objects with a physics-driven self-training neural network.

We investigate artificial-intelligence-supported in-line holographic imaging with coherent terahertz (THz) radiation. The goal is to reconstruct three...

Multiple deep learning models based on MRI images in discriminating glioblastoma from solitary brain metastases: a multicentre study.

OBJECTIVE: Development of a deep learning model for accurate preoperative identification of glioblastoma and solitary brain metastases by combining mu...

Current trends and emerging themes in utilizing artificial intelligence to enhance anatomical diagnostic accuracy and efficiency in radiotherapy.

Artificial intelligence (AI) incorporation into healthcare has proven revolutionary, especially in radiotherapy, where accuracy is critical. The purpo...