Technology | April 12, 2013

Aspect Imaging LumiQuant Enables Tomographic Quantification of Luminescence Using Compact MRI Platform

Hardware and software solution provides new multi-modality insights

Bruker Icon

April 12, 2013 — Aspect Imaging launched LumiQuantits software and hardware solution for co-registering and measuring luminescence imaging images with the Bruker Icon compact high-performance magnetic resonance imaging (MRI) system. The LumiQuant solution enables researchers to generate 3-D luminescence data co-registered with MRI, a path forward in multi-modal tomographic imaging.

LumiQuant leverages a multi-modality cassette that allows a mouse to be imaged in an optical instrument and then moved and imaged in the Bruker Icon compact MRI without perturbation. The image reconstruction and co-registration package uses a proprietary set of algorithms to create a three-dimensional distribution of luminescence signal.

Luminescence, which is the most widely used pre-clinical in vivo imaging modality for assessing pre-clinical disease models, suffers from the physical constraints of the absorption and scattering of light in tissues. This absorption and scattering hinders the ability of luminescence systems to differentiate between luminescence signal in different organs and on the surface or signal deep within the tissue and therefore limits the researcher's ability to tell whether a luminescence-expressing tumor, for example, is on the surface, is deep in the organ, is a single tumor mass or possibly is the signal expressed from multiple lesions at different positions in the body. LumiQuant seeks to resolve this obstacle through enhanced insights and quantitation of 3-D luminescence/MR imaging and disease phenotyping.

For more information: www.aspectimaging.com, www.invicro.com

Related Content

Graphic courtesy of Pixabay

Graphic courtesy of Pixabay

Feature | Artificial Intelligence | April 22, 2019 | By Greg Freiherr
...
Artificial Intelligence Performs As Well As Experienced Radiologists in Detecting Prostate Cancer
News | Artificial Intelligence | April 18, 2019
University of California Los Angeles (UCLA) researchers have developed a new artificial intelligence (AI) system to...
A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images

A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images. The algorithm, described at the SBI/ACR Breast Imaging Symposium, used “Deep Learning,“ a form of machine learning, which is a type of artificial intelligence. Graphic courtesy of Sarah Eskreis-Winkler, M.D.

Feature | Artificial Intelligence | April 12, 2019 | By Greg Freiherr
The use of smart algorithms has the potential to make healthcare more efficient.
Technological Advancements Expected to Drive Virtual Reality Growth in Healthcare
News | Advanced Visualization | April 04, 2019
Increasing demand for innovative diagnostic techniques, neurological disorders and increasing disease awareness are...
Videos | RSNA | April 03, 2019
ITN Editor Dave Fornell takes a tour of some of the most interesting new medical imaging technologies displa
Medivis Unveils AnatomyX Augmented Reality Education Platform
Technology | Advanced Visualization | April 02, 2019
Medical imaging and visualization company Medivis announced the launch of AnatomyX, its augmented reality (AR) platform...
Sponsored Content | Videos | Advanced Visualization | April 01, 2019
GE Healthcare goes beyond core equipment maintenance to help clients solve some of their most important asset and cli
Novarad Names New President
News | Enterprise Imaging | March 29, 2019
Medical imaging software company Novarad announced that it has appointed Paul Jensen as company president.