Patient Positioning Accuracy via Interest Point Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current patient positioning systems lack accuracy in determining patient posture, especially when parts of the body are covered, leading to potential errors in clinical examinations and treatments like radiotherapy, where precise positioning is crucial to avoid toxicity and improve treatment outcomes.
Innovation Solution
A system that uses an interest point detection model to acquire and compare image data from patients with pre-defined patient models, identifying matching degrees to determine a quantitative representation of the patient's posture, even when body parts are covered, and generates a scanning plan or adjusts patient positioning accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional patient positioning systems are used, then the system is simple to operate, but the positioning accuracy deteriorates when body parts are covered
Solution Approach 1:
The patent introduces an interest point detection model as an intermediary between the image data and patient positioning determination. This model automatically identifies key anatomical landmarks even when body parts are covered, serving as a mediator that bridges the gap between limited visible information and accurate positioning requirements. The model processes image data and extracts interest points that would otherwise be invisible or ambiguous, enabling accurate positioning without requiring direct visual access to all body parts.
Solution Approach 2:
The patent creates virtual copies of patient anatomy through interest point detection and matching against reference models. Instead of directly observing all body parts, the system generates a digital representation by detecting interest points in visible areas and inferring the positions of covered areas through comparison with pre-acquired reference models. This copying approach allows the system to determine positions of hidden anatomical landmarks without direct visual access.
2Measurement precision
If interest point detection model is used to identify covered body parts, then positioning accuracy is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent performs preliminary actions by pre-acquiring reference models of patient anatomy before the actual positioning task. These reference models contain pre-identified interest points and anatomical relationships that are stored for later comparison. By preparing these reference data structures in advance, the system reduces the complexity of real-time detection, as the challenging task of identifying all interest points is shifted to the offline model creation phase rather than the online measurement phase.
Solution Approach 2:
The patent implements feedback mechanisms where the interest point detection model is trained and refined using comparison between detected interest points and ground truth annotations. The system continuously improves its detection accuracy by learning from discrepancies between detected and actual interest point positions. This feedback loop enables the model to progressively reduce detection errors and improve measurement precision while managing detection complexity through iterative optimization.
3Measurement precision
If multiple patient models are compared to determine posture, then measurement precision is improved, but the loss of time increases
Solution Approach 1:
The patent segments the posture determination process into distinct stages: interest point detection from image data, comparison with multiple reference models, and final posture representation generation. By dividing the task into segments, the system can optimize each stage independently and identify the most relevant reference models for comparison rather than exhaustively processing all available models. This segmentation reduces unnecessary computations while maintaining measurement precision through targeted model comparisons.
Solution Approach 2:
The patent applies partial action by comparing image data with a selected subset of patient models rather than all possible models. The system identifies and prioritizes the most relevant reference models based on patient characteristics, anatomical similarities, or other criteria, performing detailed comparisons only with these partial set of models. This approach achieves sufficient measurement precision by focusing computational resources on the most informative comparisons rather than exhaustively processing every available model.
Data Source
AI summary
A system for patient positioning is provided. The system may acquire image data relating to a patient holding a posture and a plurality of patient models. Each patient model may represent a reference patient holding a reference posture, and include at least one reference interest point of the referent patient and a reference representation of the reference posture. The system may also identify at least one interest point of the patient from the image data using an interest point detection model. The system may further determine a representation of the posture of the patient based on a comparison between the at least one interest point of the patient and the at least one reference interest point in each of the plurality of patient models.