AIMC Topic: Molecular Imaging
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Multimodal molecular imaging in drug discovery and development.
Drug discovery today
Apr 13, 2022
In addition to individual imaging techniques, the combination and integration of several imaging techniques, so-called multimodal imaging, can provide large amounts of anatomical, functional, and molecular information accelerating drug discovery and ...
Application of artificial intelligence in brain molecular imaging.
Annals of nuclear medicine
Jan 14, 2022
Initial development of artificial Intelligence (AI) and machine learning (ML) dates back to the mid-twentieth century. A growing awareness of the potential for AI, as well as increases in computational resources, research, and investment are rapidly ...
Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells.
Communications biology
Jan 11, 2022
Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power....
High-Throughput Molecular Imaging via Deep-Learning-Enabled Raman Spectroscopy.
Analytical chemistry
Nov 19, 2021
Raman spectroscopy enables nondestructive, label-free imaging with unprecedented molecular contrast, but is limited by slow data acquisition, largely preventing high-throughput imaging applications. Here, we present a comprehensive framework for high...
Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Nov 5, 2021
The nuclear medicine field has seen a rapid expansion of academic and commercial interest in developing artificial intelligence (AI) algorithms. Users and developers can avoid some of the pitfalls of AI by recognizing and following best practices in ...
Graph of graphs analysis for multiplexed data with application to imaging mass cytometry.
PLoS computational biology
Mar 29, 2021
Imaging Mass Cytometry (IMC) combines laser ablation and mass spectrometry to quantitate metal-conjugated primary antibodies incubated in intact tumor tissue slides. This strategy allows spatially-resolved multiplexing of dozens of simultaneous prote...
Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.
Scientific reports
Mar 24, 2021
Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to ...
Complementary performances of convolutional and capsule neural networks on classifying microfluidic images of dividing yeast cells.
PloS one
Mar 17, 2021
Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. He...
Will we successfully avoid the garbage in garbage out problem in imaging data mining? An overview on current concepts and future directions in molecular imaging.
Methods (San Diego, Calif.)
Feb 13, 2021
Deep Learning-Based Annotation Transfer between Molecular Imaging Modalities: An Automated Workflow for Multimodal Data Integration.
Analytical chemistry
Feb 3, 2021
An ever-increasing array of imaging technologies are being used in the study of complex biological samples, each of which provides complementary, occasionally overlapping information at different length scales and spatial resolutions. It is important...
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