Clinical trials: CT Images
Radiation Protection
Enhancement and Restoring of Low Dose Abdominal CT Images
Through the rapid growth of multislice Computer Tomography (CT) imaging, radiation protection has become a major issue in the radiological community.
- Trial name
- NCT01059032
- Testing
- Using a 3 dimentional post processing filter
- Where
- Norway
- Volunteers
- 12 people, healthy volunteers welcome
- Sponsor
- Lars Borgen
Anatomy
Conversion of Ultrasound Images to CT Format Imaging Using Artificial Intelligence-based Learning
Background: Ultrasound imaging is an imaging method that uses sound waves to characterize the structure and function of various organs in health and disease conditions.
- Trial name
- NCT04654546
- Testing
- Ultrasound abdominal scan
- Where
- Israel
- Volunteers
- 50 people, healthy volunteers welcome
- Sponsor
- HaEmek Medical Center, Israel
AI (Artificial Intelligence), Mammary Cancer
Experiment on the Use of Innovative Computer Vision Technologies for Analysis of Medical Images in the Moscow Healthcare System
It is planned to integrate various services based on computer vision technologies for analysis of the certain type of x-ray study into Moscow Unified Radiological Information Service (hereinafter referred to as URIS).
- Conditions
- AI (Artificial Intelligence), Mammary Cancer, Lung Cancer, X-Rays; Lesion
- Trial name
- NCT04489992
- Where
- Russia
- Volunteers
- 133,000 people, healthy volunteers welcome
- Sponsor
- Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department
Accidental Falls, Loss of Muscle Strength
Interscanner Variation in Musculoskeletal Computed Tomography (CT) Measures
Maintaining strong muscles is important for the independence and quality of life in our older population. Strong muscles provide mobility and reduce the chance of falls that lead to injury.
- Trial name
- Interscanner (NCT00896415)
- Volunteers
- 20 people, healthy volunteers welcome
- Sponsor
- University of California, San Francisco
CT Images
Incisive CT Clinica Trial Protocol
The purpose of this study was to evaluate whether the new features of Incisive CT: Precise Image, (PI) and Precise Cardiac (PC) had the expected effectiveness
- Trial name
- NCT05020262
- Testing
- CT Image reconstruction
- Volunteers
- 112 people, healthy volunteers welcome
- Sponsor
- Philips Healthcare (Suzhou) Co., Ltd.
Bone Aging, Osteoporosis Diagnosis
Automated Bone Age Estimation From Noncontrast Abdominal CT Using Deep Learning
This study is a retrospective analysis that uses abdominal CT scans, which were originally taken for other medical reasons, to estimate bone age.
- Trial name
- NCT07162168
- Where
- China
- Volunteers
- 3,000 people, healthy volunteers welcome
- Sponsor
- Peking University People's Hospital
Measurements in Mandibular Symphysis
Comparison of Lateral Cephalometric and Cone Beam CT Measurements in Mandibular Symphysis
The goal of this clinical trial is to compare the linear and angular measurements of the mandibular symphyseal region using lateral cephalometric (LC) and cone beam computed tomography (CBCT) images.
- Trial name
- NCT05654844
- Testing
- LC images, CBCT images
- Where
- Turkey (Türkiye)
- Volunteers
- 100 people, healthy volunteers welcome
- Sponsor
- Ege University
Abdominal Diseases
Rapid Abdominal Diagnosis With AI & Radiology
This study aims to develop an AI-assisted diagnostic system for abdominal contrast-enhanced CT images using data from multiple inpatient centers.
- Trial name
- RADAR (NCT07040358)
- Where
- China
- Volunteers
- 2,000,000 people, healthy volunteers welcome
- Sponsor
- First Affiliated Hospital of Zhejiang University
Lung Adenocarcinoma, Radiomics
Deep Learning Signature for Predicting the Novel Grading System of Clinical Stage I Lung Adenocarcinoma
The purpose of this study is to evaluate the performance of a PET/ CT-based deep learning signature for predicting the grade 3 tumors based on the novel grading system in clinical stage stage I lung adenocarcinoma based on a…
- Conditions
- Lung Adenocarcinoma, Radiomics, Grading System
- Trial name
- NCT05736991
- Testing
- PET/CT-based Radiomics Signature
- Where
- 4 sites in China
- Volunteers
- 600 people, healthy volunteers welcome
- Sponsor
- Shanghai Pulmonary Hospital, Shanghai, China
Nasotracheal Tube Passage Through Nasal Cavity
Radiological Images for Nasotracheal Tube Size Estimation
This trial is planned to estimate the size of nasotracheal tube (NTT) by calculating the diameter of both nasal cavity in radiological images of nose (CT scan/MRI) at the level below the inferior turbinate and floor of nose in…
- Trial name
- RINSE (NCT03675698)
- Testing
- Nasotracheal Intubation
- Where
- India
- Volunteers
- 100 people, healthy volunteers welcome
- Sponsor
- Rajiv Gandhi Cancer Institute & Research Center, India
PET Images and Deep Neural Networks Algorithms
Positron Emission Tomography (PET) Images Using Deep Neural Networks
PET images are based on detecting two annihilation 511 KeV photons that are produced by positron emitting isotopes. The longer the acquisition time, the more photons are detected and processed, resulting in better image quality.
- Trial name
- NCT04140565
- Where
- Israel
- Volunteers
- 200 people, healthy volunteers welcome
- Sponsor
- Sheba Medical Center
Cancer, Lung, Cancer Liver
PixelShine vs. Iterative Reconstruction (IR) Processing of CT Images
This study will compare the quality of CT images acquired with very low-dose radiation and processed with commercially available software vs. PixelShine processed images.
- Conditions
- Cancer, Lung, Cancer Liver, X-rays; Effects
- Trial name
- NCT03033615
- Testing
- PixelShine, Conventional processing
- Volunteers
- 20 people, healthy volunteers welcome
- Sponsor
- AlgoMedica, Inc.
Cancer of the Lung, Abdominal Cancer
Investigating the Improvement in 4D CT Images Using AV Biofeedback
This study will look at how tumors in the chest and abdomen move when you breathe. Your doctors are studying if extra 4D CT scans and instructions on how to breathe can help predict this type of movement and improve the accuracy…
- Trial name
- GCC0832 (NCT00780611)
- Where
- United States
- Volunteers
- 25 people, healthy volunteers welcome
- Sponsor
- University of Maryland, Baltimore