Abstract: This disclosure relates to a rapid molecular imaging strategy that utilizes Raman spectroscopy to interrogate the molecular expression of samples, for example, histology samples. This disclosure also relates to surface-enhanced Raman spectroscopy nanoparticles (SERS-NP) as contrast agents that exhibit unsurpassed multiplexing capabilities to offer exceptional specificity. This disclosure also relates to a SERS-NP comprising a Raman active metallic core, a Raman active layer, and a shell that may offer ultra-high diagnostic sensitivity (e.g., femtomolar level). This disclosure also relates to chemically modifying these new contrast agents to target a plurality of biomarkers within the sample. This disclosure also relates to rapid assessment of the molecular expression profile of the entire sample, for example, a whole tissue section, in a single image.

Abstract: Condition detection using image processing may include receiving telemetry data related to movement of a vehicle along a vehicle path. Condition detection using image processing may further include receiving images captured by the vehicle, and generating, based on the telemetry data and the images, an altitude map for the images, and world coordinates alignment data for the images. Condition detection using image processing may further include detecting the entities in the images, and locations of the entities detected in the images, consolidating the locations of the entities detected in the images to determine a consolidated location for the entities detected in the images, generating, based on the consolidated location, a mask related to the vehicle path and the entities detected in the images, and reconstructing three-dimensional entities model for certain types of entities, based on the entities masks and world coordinates alignment data for the images.

Abstract: Condition detection using image processing may include receiving a mask generated from images and telemetry data captured by a vehicle, an altitude map, and alignment data for the mask. The images may be related to movement of the vehicle along a vehicle path and non-infrastructure entities along an infrastructure entity position of a corresponding infrastructure entity, and the telemetry data may include movement log information related to the movement of the vehicle along the vehicle path. Condition detection using image processing may further include using the mask related to the vehicle path and the non-infrastructure entities, and an infrastructure rule to detect a risk related to the infrastructure entity by analyzing the mask related to the vehicle path and the non-infrastructure entities, and the infrastructure rule, and determining whether the infrastructure rule is violated.

Abstract: Condition detection using image processing may include receiving a mask generated from images and telemetry data captured by a vehicle, an altitude map, and alignment data for the mask. The images may be related to movement of the vehicle along a vehicle path and non-infrastructure entities along an infrastructure entity position of a corresponding infrastructure entity, and the telemetry data may include movement log information related to the movement of the vehicle along the vehicle path. Condition detection using image processing may further include using the mask related to the vehicle path and the non-infrastructure entities, and an infrastructure rule to detect a risk related to the infrastructure entity by analyzing the mask related to the vehicle path and the non-infrastructure entities, and the infrastructure rule, and determining whether the infrastructure rule is violated.

Abstract: Condition detection using image processing may include receiving telemetry data related to movement of a vehicle along a vehicle path. Condition detection using image processing may further include receiving images captured by the vehicle, and generating, based on the telemetry data and the images, an altitude map for the images, and world coordinates alignment data for the images. Condition detection using image processing may further include detecting the entities in the images, and locations of the entities detected in the images, consolidating the locations of the entities detected in the images to determine a consolidated location for the entities detected in the images, generating, based on the consolidated location, a mask related to the vehicle path and the entities detected in the images, and reconstructing three-dimensional entities model for certain types of entities, based on the entities masks and world coordinates alignment data for the images.