PET/SPECT/CT preclinical imaging CUBES
Accelerate to discover
Related topics
Vizgen webinar: spatial relationships in Developmental Biology
Nov 21, 2023
MERFISH integrates spatial transcriptomics technology with high resolution spatial imaging, In this webinar we will...
Nov 14, 2023
The xCELLigence RTCA eSight enables simultaneous real time biosensor impedance-based and...
NanoCellect webinar: Plant Potential - Gentle Cell Sorting for Enhanced Plant Biology Workflows
Nov 3, 2023
Gentle cell sorting is a useful tool to increase the efficiency of plant biology workflows that include gene...
Single Cell Deposition: the cornerstone of Flow Cytometry for cellular analysis and manipulation
Nov 2, 2023
One notable technology for harnessing the power of single cell deposition is the NanoCellect WOLF G2 Cell Sorter and N1...
RareCyte webinar recording: Use of open-source software for quantitative analysis of multiplex image
Nov 1, 2023
In this webinar, Dr. McArdle describes how multiplex immunostaining is a key method for understanding spatial context...
Emulate in vivo conditions – introduce shear flow to your experiments with BioFlux system
Oct 31, 2023
Most research is still conducted in vitro without the presence of flow. We use the BioFlux System to give you the...
Single Cell Deposition: the cornerstone of Flow Cytometry for cellular analysis and manipulation
Oct 30, 2023
One notable technology for harnessing the power of single cell deposition is the NanoCellect WOLF G2 Cell Sorter and N1...
Validation of an orthotopic non-small cell lung cancer mouse model to use in radiotherapy studies
Oct 30, 2023
The use of pre-clinical orthotopic mouse models is essential for the development of novel therapies targeting solid...
Jan 31, 2023
In preclinical imaging, it is important to aim for dose reduction as longitudinal studies with many scanning time points can result in accumulated doses that impact your study results. However, lowering the dose in PET and CT imaging inherently introduces noise, and reduced image quality negatively impacts diagnostic performance. Various denoising techniques already exist, but deep learning (DL) methods have become increasingly popular for image quality enhancement.
Florence explains how she developed and evaluated an image-to-image CNN framework to predict higher quality images from noisier images acquired at lower radiation doses for both modalities.
Related technologies: PET, SPECT, CT
Get more info
Brand profile