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Clinical Trials About "Deep-Learning Image Reconstruction in CCTA" RSS

21:03 EDT 2nd April 2020 | BioPortfolio

We list hundreds of Clinical Trials about "Deep-Learning Image Reconstruction in CCTA" on BioPortfolio. We draw our references from global clinical trials data listed on ClinicalTrials.gov and refresh our database daily.

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We have published hundreds of Deep-Learning Image Reconstruction in CCTA news stories on BioPortfolio along with dozens of Deep-Learning Image Reconstruction in CCTA Clinical Trials and PubMed Articles about Deep-Learning Image Reconstruction in CCTA for you to read. In addition to the medical data, news and clinical trials, BioPortfolio also has a large collection of Deep-Learning Image Reconstruction in CCTA Companies in our database. You can also find out about relevant Deep-Learning Image Reconstruction in CCTA Drugs and Medications on this site too.

Showing "Deep Learning Image Reconstruction CCTA" Clinical Trials 1–25 of 5,400+

Extremely Relevant

Deep-Learning Image Reconstruction in CCTA

Cardiac CT allows the assessment of the heart and of the coronary arteries by use of ionising radiation. Although radiation exposure was significantly reduced in recent years, further decrease in radiation exposure is limited by increased image noise and deterioration in image quality. Recent evidence suggests that further technological refinements with artificial intelligence allows improved post-processing of images with reduction of image noise. The present study aims at as...


Breast Ultrasound Image Reviewed With Assistance of Deep Learning Algorithms

This study evaluates a second review of ultrasound images of breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by Samsung Medical Imaging, to see if this artificial intelligence will help the Radiologist make more accurate diagnoses.

Relevant

Prediction Model of CP-EBUS in the Diagnosis of Lymph Nodes

Endobronchial ultrasound (EBUS) multimodal image including grey scale, blood flow doppler and elastography, can be used as non-invasive diagnosis and supplement the pathological result, which has important clinical application value. In this study, EBUS multimodal image database of 1000 inthoracic benign and malignant lymph nodes (LNs) will be constructed to train deep learning neural networks, which can automatically select representative images and diagnose LNs. We will estab...


Analysis of Cervical Spinal MRI With Deep Learning

The aim of this study is analyzing the pathologies in cervical spinal MRI images by using image processing algorithms. Determination of these pathological cases which taught to the system with deep learning and determination of their levels. Finally; verification of the system by comparing radiologist reports and automated system outputs.

Association of Eye With Hepatobiliary Disorders :Qualitative Analysis Via Deep Learning

Artificial Intelligence and Machine Learning techniques may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in individuals with hepatobiliary disorders. We conducted a pioneer work to explore the association between the eye and liver via deep learning, to develop and evaluate different deep-learning models to predict the hepatobiliary disease by using ocular images.

Heart Rate Variability and Cognitive Load on Image-Based Virtual Reality Instructional Design in Otolaryngology

This study aims to compare heart rate variation, cognitive load, and learning outcomes of novel image-based virtual reality with traditional video in learning for otolaryngology. Half of participants will receive image-based virtual reality learning, while the other half will receive video-based learning.

Depression and Body Image Distress Following Mastectomy With Reconstruction

Mastectomy is a major surgery that can have a profound effect on women's psychosocial wellbeing, including elevated depression and body image distress. Reconstructive breast surgery aims to improve patients' psychosocial adjustment to mastectomy, yet for some women substantial distress persists after reconstruction. However, very little is known about risk or protective factors for persistent depression or body image distress following mastectomy with reconstruction. The presen...

Heuristics, Algorithms and Machine Learning: Evaluation & Testing in Radiation Therapy

The Hamlet.rt study is a prospective data collection and patient questionnaire study for patients undergoing image-guided radiotherapy with curative intent. The aim of the study is to use novel machine learning and mathematical techniques to build a model that can predict the risk of significant side effects from radiotherapy treatment for an individual patient: using calculations of normal tissue dose from radiotherapy treatment planning and patient baseline characteristics d...

Prospective Multicenter Registry On RadiaTion Dose Estimates Of Cardiac CT AngIOgraphy IN Daily Practice in 2017

The "Prospective Multicenter Registry On RadiaTion Dose Estimates Of Cardiac CT AngIOgraphy IN Daily Practice in 2017" (PROTECTION-VI) study is a prospective registry and investigator-initiated initiative without third-party funding, which will collect and analyze the radiation dose exposure of Cardiac Computed Tomography Angiographic (CCTA) studies in current daily practice worldwide. Particularly, the study will assess the use of strategies for dose reduction during CCTA. ...

Diagnostic Performance of Deep Learning for Angle Closre

Primary angle closure diseases (PACD) are commonly seen in Asia. In clinical practice, gonioscopy is the gold standard for angle width classification in PACD patietns. However, gonioscopy is a contact examination and needs a long learning curve. Anterior segment optical coherence tomography (AS-OCT) is a non-contact test which can obtain three dimensional images of the anterior segment within seconds. Therefore, we designed the study to verify if AS-OCT based deep learning algo...

Deep-learning Based Location of Spine CT

CT-guided epidural steroid injection (ESI) thrives among interventional radiologists. Although X-ray fluoroscopy still remains as the gold standard to guide ESI, CT guidance has the merits of accurate location of needle tip and relatively low radiation doses with intermittent mode. However, it is time-consuming for doctors to select the optimal plane for needle placement and manually segment spinal structures. The main of the study is to automatically identify the optimal plane...

Study in Subjects Suspected of Having CAD Undergoing VISIPAQUE-enhanced CCTA as Part of Their Routine Medical Care

To assess prognostic value of CCTA examination in subjects who undergo CCTA as part of their medical care when compared to a standard of truth, i.e. subject outcomes during each follow-up period.

A Clinical Study of TRUVIEW ART™(Advanced Reconstruction Tech)to Improve Image Quality on Chest Radiograph

To validate the following theory: "With TRUVIEW ART™ applied a detector's quantitative performance index, MTF(Modulation Transfer Function), is increased 20% or more". This is to examine the effect of the increased MTF index, whether it influences or not the interpreter's preference

C-arm Computed Tomography Scan Image Quality in Patients With Neurovascular Diseases

With new developments that have taken place in the optimization of C-arm computed tomography (CACT) image acquisition and reconstruction, CACT image quality will be better than current standard-of-care CACT scan techniques used for neurovascular patients referred to endovascular treatment or diagnosis. As such, novel acquisition, filtration, artifact reduction and reconstruction techniques will be evaluated against the standard-of-care CACT approach.

Assessment of Change in Atherosclerotic Plaque by Serial CCTA

Assessment of Change in AtheROSclerotic Plaque by Serial CCTA (ACROSS) is designed as a prospective observational study which aim is to demonstrate the effect of statins on coronary atherosclerosis, assessed by quantitative analysis of CCTA.

AI-Assisted Facial Surgical Planning

Computer vision using deep learning architecture is broadly used in auto-recognition. In the research, the deep learning model which is trained by categorized single-eye images is applied to achieve the good performance of the model in blepharoptosis auto-diagnosis.

Impact of Reconstruction Method (ASIR, FBP) Used in CT on Bone SPECT/CT Image Quality

The main objective of this study is to demonstrate the non-inferiority of SPECT image quality (as measured by the signal / noise ratio) obtained by ASIR reconstruction of very-low-dose CT acquisitions versus the quality of those obtained by filtered back projection (FBP) of low-dose CT acquisitions. The lower limit of non-inferiority is set to -1, the average SPECT signal / noise ratio TEMP expected is between 5 and 6.

Artificial Intelligence Identifying Polyps in Real-world Colonoscopy

Recently, artificial intelligence (AI) assisted image recognition has made remarkable breakthroughs in various medical fields with the developing of deep learning and conventional neural networks (CNNs). However, all current AI assisted-diagnosis systems (ADSs) were established and validated on endoscopic images or selected videos, while its actual assisted-diagnosis performance in real-world colonoscopy is up to now unknown. Therefore, we validated the performance of an ADS in...

Cardiac Computed Tomography In the Management of Patients With indeterminAte or inConclusive Stress Tests

Coronary CT angiography (CCTA) offers great promise as a risk stratification tool in patients with suspected CAD. It has been demonstrated in a multitude of accuracy studies to have a negative predictive value averaging over 95%. This leads to the hypothesis that a negative CCTA may preclude the need for invasive testing. The purpose of this randomized controlled study is to prospectively evaluate the role of CCTA on the management of patients with inconclusive or indeterminat...

Ongoing Registry of Deep Venous Reconstructions

Ongoing registration of deep venous obstructive disease patients treated by means of percutaneous transluminal angioplasty (PTA) and stenting with or without endophlebectomy (surgical desobstruction, also termed endovenectomy) of the common femoral vein and/or arteriovenous fistula creation.

Evaluation of Agreement Between CT Scan and 3D-DXA Measurements on the Lombar Spine

Dual-energy X-ray Absorptiometry is frequently used to measure bone mineral density. A new medical device, Box 3D DXA, creates a 3D image using a statistics reconstruction model developed on the femur. This new imaging technique does not require additional irradiation and ought to improve bone measures as well as incorporating densitometric parameters into the diagnosis. This study will test the reconstruction of the 3D image from lombar spine measurements and compare accuracy ...

CCTA-FFR Registry for Risk Prediction

The investigators sought to investigate the prognostic implication of qualitative and quantitative plaque analysis on coronary CT angiography (CCTA) according to fractional flow reserve (FFR). The main objective was to develop a comprehensive risk model by using clinical risk factors, FFR and CCTA parameters.

Quality of Life, Aesthetic Result and Health Economy in Breast Reconstruction

A randomized clinical trial with two arms: irradiated women and non-irradiated women. Irradiated women are randomized to reconstruction with a latissimus Dorsi flap and an implant or a deep inferior epigastria perforator flap. Non-irradiated women are randomized to reconstruction with a thoracodorsal flap with an implant or with an expander and later a permanent implant in two stages.

Case Series Comparing Drains to TissuGlu® in a Donor Site DIEP Flap Breast Reconstruction Procedure

To evaluate the safety and effectiveness of a lysine-derived urethane adhesive (TissuGlu® Surgical Adhesive) as a less invasive alternative to surgical drains in the abdominal donor site for deep inferior epigastric perforator (DIEP) flap reconstruction.

Protocol for Evaluation of Quarter-Time Cardiac Imaging: 5-Minutes Rest and 3-Minutes Stress Wide Beam Reconstruction (WBR) Versus Full-Time Filtered Back Projection (FBP)

A new, innovative software image processing method, wide beam reconstruction (WBR), utilizes resolution recovery and incorporates Poisson noise-reduction into the reconstruction process of NM images. This method facilitates the reconstruction of low count density myocardial perfusion SPECT images. Preliminary research indicates that SPECT acquisition time consequently can be reduced by 60% (less than 5 minutes) for rest and by 75% (just over 3 minutes) for stress, while tomogr...


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