Camera-based Navigation
Camera-based Navigation - Related Videos
05:19
Practical Methodology of Cognitive Tasks Within a Navigational Assessment
0 Views •
Cited by 1 •
2015
Children who have complex communication needs can benefit from the use of a speech-generating device (SGD). Cognitive skills were identified as having an impact on the ability to navigate between levels of SGDs. This protocol describes the steps needed for Speech-language Pathologists to assess cognitive skills and navigational abilities.
08:12
Two-photon Calcium Imaging in Mice Navigating a Virtual Reality Environment
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Cited by 98 •
2014
Here we describe the experimental procedures involved in two-photon imaging of mouse cortex during behavior in a virtual reality environment.
02:23
Navigational Behavior of Drosophila Larvae in Response to Optogenetic Stimulation of Olfactory Sensory Neurons
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2025
This video demonstrates a study of the navigational behavior of Drosophila larvae in response to optogenetic stimulation of olfactory sensory neurons (ORNs). Transgenic Drosophila larvae expressing light-sensitive ion channels in the ORNs are placed on agarose within a behavior arena. Optogenetic stimulation with light opens the channels, causing a cation influx that triggers the transmission of the signal to the brain, and the navigation behavior is recorded.
07:41
RGBradford: Protein Quantitation with a Smartphone Camera
0 Views •
2023
This paper provides a protocol for protein quantification using the Bradford assay and a smartphone as an analytical device. Protein levels in samples can be quantified using color data extracted from a picture of a microplate taken with a smartphone.
06:03
Use of Electromagnetic Navigational Transthoracic Needle Aspiration (E-TTNA) for Sampling of Lung Nodules
0 Views •
Cited by 12 •
2015
We describe the novel use of electromagnetic navigational guided transthoracic needle aspiration for the pathologic assessment of human lung nodules.
FAQs
Sequential image analysis supplies motion cues by comparing visual features across successive frames. The system tracks how identifiable points or structures change position, then uses those changes to estimate movement relative to the surrounding environment. This process supports position and orientation estimates even when direct measurement is limited, providing the basis for guidance during image-guided medical procedures.
Image registration aligns information from different visual or anatomical sources into a related spatial framework. In medicine, this can connect a camera view with patient anatomy or a preoperative image, allowing the system to interpret instrument motion in relation to the intended treatment area. The resulting correspondence supports more precise guidance than viewing camera images without anatomical linkage.
Real-time feedback lets the system update guidance as the camera view and tracked features change. This continuous response helps reflect ongoing instrument or robotic movement rather than relying on a fixed image relationship. In surgical and endoscopic settings, updated spatial information can improve awareness of the procedure as it unfolds and support more controlled interaction with patient anatomy.
A typical workflow begins with camera image capture, followed by identification and tracking of visual features across sequential frames. The system then estimates position, orientation, and movement, applies image registration when camera views must be related to anatomy or preoperative images, and provides real-time guidance. These linked stages turn visual observations into actionable navigation information.
The approach can support surgical instrument guidance, endoscopic procedures, and robotic medical systems. Its role is to relate camera observations to the operative environment, patient anatomy, or planned imaging information. This makes it relevant to minimally invasive care, where direct access and direct measurement may be limited and spatial awareness is especially important for guiding instruments.
Image registration provides the connection between a live camera view and information obtained before a procedure. By relating the visual scene to patient anatomy or a preoperative image, the system can place instrument motion within a clinically meaningful spatial context. This linkage helps clinicians use prior anatomical information while responding to the current camera view during treatment.
Camera-based navigation may improve spatial awareness and procedural precision while supporting minimally invasive care. It also contributes to image-guided therapy by connecting visual information with anatomy and instrument motion. Beyond clinician-assisted procedures, the same principles advance robotic and autonomous medical technologies that require ongoing visual information to navigate within a patient-related environment.