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...

You might also read

Related Articles

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

Sort by

Same author

Immunosuppressive therapies adversely affect blood biochemical parameters in patients with inflammatory bowel disease: a meta-analysis.

The Journal of international medical research·2019

Same author

Facile synthesis of Ag-CuO/SBA-15 for aerobic epoxidation of olefins with high activity.

Nanotechnology·2019

Same author

Reinforcement of Polylactic Acid for Fused Deposition Modeling Process with Nano Particles Treated Bamboo Powder.

Polymers·2019

Same author

Comparison of deep learning and human observer performance for detection and characterization of simulated lesions.

Journal of medical imaging (Bellingham, Wash.)·2019

Same author

Bending Flexibility of Moso Bamboo (<i>Phyllostachys Edulis</i>) with Functionally Graded Structure.

Materials (Basel, Switzerland)·2019

Same author

CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE).

IEEE transactions on medical imaging·2019

Same journal

Non-locking Tetrahedral Finite Element for Surgical Simulation.

Communications in numerical methods in engineering·2015

Same journal

Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction.

Communications in numerical methods in engineering·2011

Same journal

Surface Smoothing and Quality Improvement of Quadrilateral/Hexahedral Meshes with Geometric Flow.

Communications in numerical methods in engineering·2011

Same journal

An integrated solution and analysis of bioluminescence tomography and diffuse optical tomography.

Communications in numerical methods in engineering·2011

Same journal

Computational methods for optical molecular imaging.

Communications in numerical methods in engineering·2010

Same journal

A Parallel Adaptive Finite Element Method for the Simulation of Photon Migration with the Radiative-Transfer-Based Model.

Communications in numerical methods in engineering·2010

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 16, 2026

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

Published on: January 12, 2013

Interior SPECT- Exact and Stable ROI Reconstruction from Uniformly Attenuated Local Projections.

Hengyong Yu¹, Jiansheng Yang, Ming Jiang

¹CT Laboratory, Biomedical Imaging Division, VT-WFU School of Biomedical Engineering Virginia Tech, Blacksburg, VA 24061, USA.

Communications in Numerical Methods in Engineering

|February 18, 2010

Summary

This summary is machine-generated.

This study introduces interior single photon emission computed tomography (SPECT) for precise region of interest reconstruction using limited projection data. The method proves exact and stable, even with partial data, aiding biomedical imaging applications.

More Related Videos

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

Published on: November 16, 2019

Related Experiment Videos

Last Updated: Jun 16, 2026

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

Published on: January 12, 2013

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

Published on: November 16, 2019

Area of Science:

Biomedical Imaging
Medical Physics
Tomography

Background:

Single photon emission computed tomography (SPECT) is a vital biomedical imaging technique.
The use of truncated projection data in SPECT is common due to equipment constraints (expensive, bulky gamma cameras).
Existing methods struggle with accurate reconstruction from incomplete data.

Purpose of the Study:

To develop an interior SPECT approach for exact and stable reconstruction of a region of interest (ROI).
To address the challenge of reconstructing from uniformly attenuated local projection data.
To leverage prior knowledge of a sub-region within the ROI for improved accuracy.

Main Methods:

Analytic continuation and singular value decomposition (SVD) were used to prove exactness and stability.
Reconstruction involves inverting a generalized truncated Hilbert transform.
The method utilizes constant attenuation coefficients and known object boundaries.
Prior knowledge of a sub-region within the ROI is incorporated.

Main Results:

The interior SPECT method is demonstrated to be both exact and stable.
Singular value decomposition (SVD) confirms the stability of the interior SPECT reconstruction.
Preliminary numerical simulations show practical utility for the proposed method.

Conclusions:

The interior SPECT approach enables accurate and stable image reconstruction from limited, truncated projection data.
This method offers a viable solution for scenarios where full data acquisition is not feasible.
Future work includes generalizing the method to handle variable attenuation coefficients.