Lung Cancer

Cardiac substructure segmentation with deep learning for improved cardiac sparing.

PURPOSE: Radiation dose to cardiac substructures is related to radiation-induced heart disease. However, substructures are not considered in radiation therapy planning (RTP) due to poor visualization on CT. Therefore, we developed a novel deep learning (DL) pipeline leveraging MRI's soft tissue contrast coupled with CT for state-of-the-art cardiac substructure segmentation requiring a single, non-...

Presence of pyrroloquinazoline alkaloid in attenuates inflammatory response through the downregulation of pro-inflammatory mediators in LPS stimulated RAW 264.7 macrophages.

Inflammation is the primary response caused due to harmful stimuli which are followed by the increased draining of plasma and immune cells from the body into the site of the injured tissue. A signaling cascade of growth factors and cytokines propagates and eventually matures in the inflammatory site involving the blood vessels and immune markers within the injured tissue in order to promote the r...

Discontinuation of Proton Pump Inhibitors in Patients With Chronic Kidney Disease.

Proton pump inhibitors (PPIs) are commonly used medications and are historically well tolerated. Recent studies have linked PPI use to the developmen...

Contrast enhanced oesophageal avoidance for stereotactic body radiotherapy: Barium vs. Gastrografin.

INTRODUCTION: SABR may facilitate treatment in a greater proportion of locally-advanced NSCLC patients, just as it has for early-stage disease. The oe...

Multi-objective ensemble deep learning using electronic health records to predict outcomes after lung cancer radiotherapy.

Accurately predicting treatment outcome is crucial for creating personalized treatment plans and follow-up schedules. Electronic health records (EHRs)...

Development of a robot-assisted ultrasound-guided radiation therapy (USgRT).

PURPOSE: Radiation treatment is improved by the use of image-guided workflows. This work pursues the approach of using ultrasound (US) as a real-time ...

Hollow Alginate-Poly-L-Lysine-Alginate Microspheres Promoted an Epithelial-Mesenchymal Transition in Human Colon Adenocarcinoma Cells.

Today, there is an urgent need to develop a three-dimentional culture systems mimicking native condition in order to screen potency of drugs and pos...

A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.

OBJECTIVE: To develop a deep learning-based artificial intelligence (AI) scheme for predicting the likelihood of the ground-glass nodule (GGN) detecte...

Predictive models for patients with lung carcinomas to identify EGFR mutation status via an artificial neural network based on multiple clinical information.

PURPOSE: Epidermal growth factor receptor (EGFR) mutation testing has several limitations. Therefore, we built predictive models to determine the EGFR...

Twin Robotic X-Ray System for 3D Cone-Beam CT of the Wrist: An Evaluation of Image Quality and Radiation Dose.

The purpose of this study was to assess image quality and radiation dose of a novel twin robotic x-ray system's 3D cone-beam CT (CBCT) function for t...

The integrative knowledge base for miRNA-mRNA expression in colorectal cancer.

"miRNA colorectal cancer" (https://mirna-coadread.omics.si/) is a freely available web application for studying microRNA and mRNA expression and their...

The role of artificial intelligence in medical imaging research.

Without doubt, artificial intelligence (AI) is the most discussed topic today in medical imaging research, both in diagnostic and therapeutic. For dia...

Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer.

BACKGROUND: Accurate and standardized descriptions of organs at risk (OARs) are essential in radiation therapy for treatment planning and evaluation. ...

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer.

Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation...

ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network.

BACKGROUND: The spatial distributions of different types of cells could reveal a cancer cell's growth pattern, its relationships with the tumor microe...

Deep segmentation networks predict survival of non-small cell lung cancer.

Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide...

Artificial intelligence based approaches to evaluate actual evapotranspiration in wetlands.

Wetlands are extraordinary ecosystems and important climate regulators that also contribute to reduce natural disaster risk. Unfortunately, wetlands a...

Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.

PURPOSE: Acute ischemic stroke is one of the most causes of death all over the world. Onset to treatment time is critical in stroke diagnosis and trea...

Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.

Tomographic imaging using penetrating waves generates cross-sectional views of the internal anatomy of a living subject. For artefact-free volumetric ...

Identification of genes of four malignant tumors and a novel prediction model development based on PPI data and support vector machines.

Triple-negative breast cancer (TNBC), colon adenocarcinoma (COAD), ovarian cancer (OV), and glioblastoma multiforme (GBM) are common malignant tumors,...