TriDFusion (3DF) image viewer | JoVE Visualize

TriDFusion (3DF) image viewer

Daniel Lafontaine¹, C Ross Schmidtlein², Assen Kirov²

¹Departments of Medical Physics, Memorial Sloan Kettering Cancer Center, 1250 First Avenue, New York, NY, 10065, USA. lafontad@mskcc.org.

EJNMMI Physics|October 18, 2022

View abstract on PubMed

Summary

The TriDFusion (3DF) image viewer is an open-source platform for nuclear medicine research, offering advanced tools for multi-modality image analysis and fusion. It provides researchers with capabilities beyond commercial workstations for enhanced imaging studies.

Area of Science:

Medical Imaging
Nuclear Medicine
Computational Biology

Background:

Nuclear medicine research often faces limitations with existing commercial workstations.
There is a need for advanced, extensible imaging tools tailored for research applications.

Purpose of the Study:

To introduce the TriDFusion (3DF) image viewer, an open-source platform designed to meet unmet needs in nuclear medicine research.
To provide researchers with a versatile tool for multi-modality image analysis and fusion.

Main Methods:

Developed an open-source, extensible medical viewing platform (TriDFusion/3DF).
Integrated image registration for multiple modalities with volumes of interest (VOIs) and dose distributions.
Included functionalities for image display, multi-image fusion, segmentation, dosimetry, and error correction.
Developed using MATLAB for readability and ease of modification.

Main Results:

The 3DF viewer supports registration of multi-modal images with VOIs and dose distributions.
It offers vendor-neutral processing of images from different systems.
Key features include a high-quality viewer, multi-image fusion, segmentation tools, dosimetry calculators, and clinical correction tools.
Results can be saved as DICOM files or exported as CSV data.

Conclusions:

TriDFusion (3DF) is a powerful, user-friendly, open-source imaging research tool for the nuclear medicine community.
It enables physicians, medical physicists, and researchers to effectively display, manipulate, and analyze medical images.
The platform enhances capabilities for complex research workflows in nuclear medicine.

Keywords: