Landmark Digitization
Landmark Digitization - Related Videos
04:47
Systematic Bronchoscopy: the Four Landmarks Approach
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Cited by 4 •
2023
Here, we present a protocol to navigate the bronchial maze in a structured manner, splitting the bronchoscopy into a stepwise approach-the four landmarks approach.
05:22
Systematic Endobronchial Ultrasound - The Six Landmarks Approach
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Cited by 1 •
2023
Endobronchial ultrasound-guided sampling using transbronchial needle aspiration plays a key role in staging and diagnosing lung cancer. We propose a systematic stepwise approach dividing the procedure into six landmarks that should be taught to new operators.
08:06
Use of a Low-flow Digital Anesthesia System for Mice and Rats
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Cited by 4 •
2016
Here, we present a protocol to more safely and efficiently administer anesthetic gas to mice using a digital, low flow anesthesia system utilizing a syringe-driven direct injection vaporizer.
10:55
Digital Microfluidics for Automated Proteomic Processing
0 Views •
Cited by 30 •
2009
Digital Microfluidics is a technique characterized by the manipulation of discrete droplets (~nL - mL) on an array of electrodes by the application of electrical fields. It is well-suited for carrying out rapid, sequential, miniaturized automated biochemical assays. Here, we report a platform capable of automating several proteomic processing steps.
14:02
Measuring Engagement of Spectators of Social Digital Games
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2021
We propose a methodology that enables measuring engagement of spectators in a social digital game combining physiological and self-reported data. As this digital game involves a group of freely moving people, the experience is filmed using a synchronizing technique that links physiological data with events in the game.
FAQs
Consistency determines whether measurements represent true anatomical differences or simply differences in how points were chosen. Using the same anatomical reference features across images or patient models makes coordinate-based comparisons more reproducible. This is especially important when researchers evaluate anatomical variation, growth, or treatment outcomes, because inconsistent point placement can weaken geometric analysis and obscure meaningful changes.
Landmark coordinates provide corresponding spatial reference points that computational methods can use to compare images or three-dimensional models. When the same anatomical features are recorded across datasets, their positions help relate one model to another and quantify shape or location differences. This creates a measurable connection between visual anatomy, image registration, and computational modeling.
Suitable references depend on the clinical or research question and may include bone edges, joint centers, or soft-tissue points. These features provide recognizable locations for measuring anatomy in a consistent coordinate framework. Selecting references that match the structure being studied allows the resulting data to support comparisons of anatomical variation, development, or changes associated with treatment.
A typical workflow begins by examining a medical image or three-dimensional patient model and identifying the anatomical features relevant to the study. The selected points are then marked and assigned spatial coordinates. Those coordinates can be organized for geometric analysis, comparison between cases, image registration, or evaluation of anatomical change, depending on the research objective.
By converting selected anatomical features into spatial data, the technique gives clinicians and researchers a quantitative framework for examining patient-specific anatomy. These measurements can support geometric assessment and computational modeling before an intervention. In that context, digitized landmarks help connect diagnostic imaging with planning approaches that account for individual anatomical structure rather than relying only on general visual impressions.
Researchers can record corresponding landmarks at different stages and compare their coordinates to assess anatomical change over time. This supports quantitative evaluation of growth, variation, or response to treatment rather than relying solely on descriptive observations. The resulting measurements can also improve reproducibility when studies compare multiple patients, images, or three-dimensional models.