Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Computed Tomography01:10

Computed Tomography

4.6K
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...
4.6K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

28
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...
28
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.4K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.4K

You might also read

Related Articles

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

Sort by
Same author

Biodegradable lipid nanoparticles for genome editing in the brain via intrathecal administration.

Materials today (Kidlington, England)·2026
Same author

Spatial transcriptomics identifies immune-stromal niches associated with cancer in adult dermatomyositis.

Nature communications·2026
Same author

SynReEM: Synapse Reconstruction via Instance Structure Encoding in Anisotropic Electron Microscopic Volumes.

IEEE transactions on medical imaging·2026
Same author

Corrigendum to 'Establishment and characterization of an inflammatory cartilaginous organoids model for organoid transplantation study' [J Orthop Transl 52, May 2025, Pages 376-386].

Journal of orthopaedic translation·2026
Same author

Spatial transcriptomics identifies cytotoxic and fibrotic immune-stromal niches in morphea and eosinophilic fasciitis.

The Journal of investigative dermatology·2026
Same author

The Use of Single-Cell Mitochondrial DNA SNP Combinations for Distinguishing Organ-Specific Cell Types.

Cells·2026

Related Experiment Video

Updated: Jul 21, 2025

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals
07:57

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals

Published on: April 25, 2017

8.4K

Edge-Enhanced Object-Space Model Optimization of Tomographic Reconstructions for Additive Manufacturing.

Yanchao Zhang1, Minzhe Liu2, Hua Liu3

  • 1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CAS), Changchun 130033, China.

Micromachines
|July 29, 2023
PubMed
Summary

An improved Object-Space Model Optimization (OSMO) algorithm enhances additive manufacturing accuracy for tomographic reconstructions. This new approach refines boundary edges, significantly boosting reconstruction quality and convergence performance.

Keywords:
OSMOedge enhancedoptimizationtomographic reconstructionvolumetric additive manufacturing

More Related Videos

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing
11:36

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

Published on: February 9, 2022

2.8K
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.8K

Related Experiment Videos

Last Updated: Jul 21, 2025

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals
07:57

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals

Published on: April 25, 2017

8.4K
Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing
11:36

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

Published on: February 9, 2022

2.8K
Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
09:10

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Published on: August 5, 2021

1.8K

Area of Science:

  • Additive Manufacturing
  • Computational Imaging
  • Image Reconstruction

Background:

  • Object-space model optimization (OSMO) is an effective method for additive manufacturing of tomographic reconstructions.
  • Existing OSMO methods offer good accuracy but can be further refined for boundary precision.

Purpose of the Study:

  • To introduce an improved Object-Space Model Optimization (OSMO) algorithm for enhanced additive manufacturing accuracy.
  • To refine the reconstruction of target boundaries in tomographic models.

Main Methods:

  • An enhanced OSMO algorithm incorporating two additional steps per iteration: enhancing in-part edges and weakening out-of-part edges.
  • Definition of a new quality metric, 'Edge Error', for volumetric printing.
  • Testing the algorithm on diverse exemplary geometries.

Main Results:

  • Significant improvements in quality metrics including Volume Error (VER), প্রিন্টability Weight (PW), and In-Part Density Ratio (IPDR).
  • Substantial reduction in the newly defined 'Edge Error' metric.
  • Demonstrated superior convergence and accuracy compared to the standard OSMO approach.

Conclusions:

  • The improved OSMO algorithm offers enhanced accuracy and convergence for additive manufacturing of tomographic reconstructions.
  • The new 'Edge Error' metric effectively quantifies boundary reconstruction quality.
  • This refined approach represents a significant advancement in volumetric printing accuracy.