Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Computed Tomography

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...

Imaging Studies III: Computed Tomography

Imaging Studies III: Computed Tomography

DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...

Imaging Studies for Cardiovascular System V: CT

Imaging Studies for Cardiovascular System V: CT

Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...

Imaging Studies I: CT and MRI

Imaging Studies I: CT and MRI

Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Spectral deep learning-based patient and bowtie scatter correction for clinical photon-counting CT.

Medical physics·2026

Same author

Detection of calcified plaques: comparison between coronary CT angiography and thin-slice non-contrast CT with deep learning-aided image registration.

European radiology·2026

Same author

Feasibility of opportunistic dental diagnostics in routine photon-counting CT examinations of the cervical spine.

BMC oral health·2026

Same author

Lung cancer screening CT acquisition protocols for three generations of CT systems conforming to German legislation.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2025

Same author

Deep learning in CT image reconstruction and processing: techniques, performance evaluation, radiation dose, and future perspective.

The British journal of radiology·2025

Same author

Spectral CT in practice: insights from an International Atomic Energy Agency survey.

Insights into imaging·2025

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Contrast Enhanced Vessel Imaging using MicroCT

Contrast Enhanced Vessel Imaging using MicroCT

Published on: January 27, 2011

Improved total variation-based CT image reconstruction applied to clinical data.

Ludwig Ritschl¹, Frank Bergner, Christof Fleischmann

¹Institute of Medical Physics (IMP), University of Erlangen-Nürnberg, Erlangen, Germany. ludwig.ritschl@imp.uni-erlangen.de

Physics in Medicine and Biology

|February 18, 2011

Summary

This study introduces a new compressed sensing method for computed tomography reconstruction using limited raw data. The novel algorithm effectively reduces image artifacts without prior data knowledge, achieving fast convergence across various challenging scenarios.

More Related Videos

Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation

Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation

Published on: June 3, 2018

Related Experiment Videos

Last Updated: Jun 4, 2026

Contrast Enhanced Vessel Imaging using MicroCT

Contrast Enhanced Vessel Imaging using MicroCT

Published on: January 27, 2011

Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation

Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation

Published on: June 3, 2018

Area of Science:

Medical Imaging
Image Reconstruction
Computational Science

Background:

Computed tomography (CT) often requires image reconstruction from limited raw data.
Compressed sensing (CS) algorithms, utilizing the ℓ(1)-norm cost function, show promise in handling incomplete datasets.
Existing heuristic optimization methods often alternate between optimizing raw data and sparsity cost functions.

Purpose of the Study:

To present a novel method for adapting optimization steps in CT reconstruction from limited data.
To improve convergence and artifact reduction without requiring a priori knowledge of raw data consistency.
To evaluate the proposed method's performance in diverse clinical scenarios.

Main Methods:

A new alternating optimization strategy is proposed, adapting step-size determination in the raw data domain.
The method ensures convergence to the lowest raw data cost function value while maintaining low sparsity.
Evaluation involves processing clinical datasets with angular undersampling, metal artifacts, limited view angles, and interior tomography.

Main Results:

The proposed method converges within 25 iterations using constant control parameters.
Significant reduction in image artifacts caused by incomplete raw data was observed.
No new artifacts, such as staircasing, were introduced.
Performance was compared favorably against the ASD-POCS algorithm.

Conclusions:

The novel method offers an effective solution for CT reconstruction with limited raw data.
It demonstrates robustness and efficiency across various challenging imaging situations.
The algorithm allows for easy incorporation of additional prior information, similar to the PICCS algorithm.