Lung Cancer

Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer.

BACKGROUND: Dose escalation radiotherapy enables increased control of prostate cancer (PCa) but requires segmentation of dominant index lesions (DIL). This motivates the development of automated methods for fast, accurate, and consistent segmentation of PCa DIL.

Equivalent radiation exposure with robotic total hip replacement using a novel, fluoroscopic-guided (CT-free) system: case-control study versus manual technique.

Accurate and precise positioning of the acetabular cup remains a prevalent challenge in total hip arthroplasty (THA). Robotic assistance for THA has increased over the past decade due to the potential to improve the accuracy of implant placement. However, a common criticism of existing robotic systems is the requirement for preoperative computerized tomography (CT) scans. This additional imaging i...

Validation of a Fully Automated Hybrid Deep Learning Cardiac Substructure Segmentation Tool for Contouring and Dose Evaluation in Lung Cancer Radiotherapy.

BACKGROUND AND PURPOSE: Accurate and consistent delineation of cardiac substructures is challenging. The aim of this work was to validate a novel segm...

Unpaired low-dose computed tomography image denoising using a progressive cyclical convolutional neural network.

BACKGROUND: Reducing the radiation dose from computed tomography (CT) can significantly reduce the radiation risk to patients. However, low-dose CT (L...

Evaluation of deep learning based implanted fiducial markers tracking in pancreatic cancer patients.

Real-time target position verification during pancreas stereotactic body radiation therapy (SBRT) is important for the detection of unplanned tumour m...

Orthopedic Robot-Assisted Femoral Neck System in the Treatment of Femoral Neck Fracture.

Cannulated screw fixation is the main therapy for femoral neck fractures, especially in young patients. The traditional surgical procedure uses C-arm ...

Computed Tomography of the Head : A Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

In 1971, the first computed tomography (CT) scan was performed on a patient's brain. Clinical CT systems were introduced in 1974 and dedicated to head...

Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate...

Computed tomography and radiation dose images-based deep-learning model for predicting radiation pneumonitis in lung cancer patients after radiation therapy.

PURPOSE: To develop a deep learning model that combines CT and radiation dose (RD) images to predict the occurrence of radiation pneumonitis (RP) in l...

Initial perioperative outcomes of robot-assisted thoracoscopic lobectomy using a confronting setting.

PURPOSE: Most robot-assisted thoracoscopic surgery (RATS) is performed from the vertical view. This study evaluates the initial outcomes of our novel ...

Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images.

 Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate segmentation of the primary tumor (GTVp) of oroph...

Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow.

. The purpose of this study was to evaluate the accuracy of brachytherapy (BT) planning structures derived from Deep learning (DL) based auto-segmenta...

Gene-environment interaction analysis via deep learning.

Gene-environment (G-E) interaction analysis plays an important role in studying complex diseases. Extensive methodological research has been conducted...

Image-based scatter correction for cone-beam CT using flip swin transformer U-shape network.

BACKGROUND: Cone beam computed tomography (CBCT) plays an increasingly important role in image-guided radiation therapy. However, the image quality of...

Sooty Tern Optimization Algorithm-Based Deep Learning Model for Diagnosing NSCLC Tumours.

Lung cancer is one of the most common causes of cancer deaths in the modern world. Screening of lung nodules is essential for early recognition to fac...

Robot-assisted versus laparoscopic distal pancreatectomy: a systematic review and meta-analysis including patient subgroups.

BACKGROUND: Robot-assisted distal pancreatectomy (RDP) has been suggested to hold some benefits over laparoscopic distal pancreatectomy (LDP) but cons...

Reducing both radiation and contrast doses for overweight patients in coronary CT angiography with 80-kVp and deep learning image reconstruction.

PURPOSE: To investigate the use of an 80-kVp tube voltage combined with a deep learning image reconstruction (DLIR) algorithm in coronary CT angiograp...

Synthetic cranial MRI from 3D optical surface scans using deep learning for radiation therapy treatment planning.

BACKGROUND: Optical scanning technologies are increasingly being utilised to supplement treatment workflows in radiation oncology, such as surface-gui...

Deep learning model integrating positron emission tomography and clinical data for prognosis prediction in non-small cell lung cancer patients.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide. The majority of lung cancers are non-small cell lung cancer (NSCLC), ...

Machine intelligence for radiation science: summary of the Radiation Research Society 67th annual meeting symposium.

The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcom...