Design and Interpretation of a Convolutional Neural Network Architecture for Imaging Mass Spectrometry Data

Convolutional Neural Networks (CNNs) have emerged primarily from research focusing on image classification tasks and as a result, most of the well-motivated design choices found in literature are relevant to computer vision applications. CNNs' application on Imaging Mass Spectrometry (IMS) data is quite recent and involves new challenges, such...

Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration

Introduction: Age related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone and rod photoreceptor functions and strongly...

Visualizing Staphylococcus aureus pathogenic membrane modification within the host infection environment by multimodal imaging mass spectrometry

Bacterial pathogens have evolved virulence factors to colonize, replicate, and disseminate within the vertebrate host. Although there is an expanding body of literature describing how bacterial pathogens regulate their virulence repertoire in response to environmental signals, it is challenging to directly visualize virulence response within...

Surface Analysis Techniques in Forensic Science: Successes, Challenges, and Opportunities for Operational Deployment

Surface analysis techniques have rapidly evolved in the last decade. Some of these are already routinely used in forensics, such as for the detection of gunshot residue or for glass analysis. Some surface analysis approaches are attractive for their portability to the crime scene. Others can be very helpful in forensic laboratories owing to...

On the Atoms of Robustness: Robust Matrix Decomposition for Spectral Imaging

Modern imaging modalities across many application domains increasingly acquire a large number of very high-dimensional measurements, commonly collecting hundreds to millions of variables per spatial resolution element. That high-dimensional nature can severely challenge traditional (often Euclidean distance based) approaches to noise and...

Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry

Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a large number of ions concurrently in a single experiment. While this makes it particularly suited...