Interactive 3D Segmentation via Dynamic Parameter Adjustment
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Solution Overview
Problem
Current image segmentation technologies require manual reconfiguration and repeated processing steps to achieve satisfactory results, which is time-consuming and cumbersome, as users must manually adjust segmentation parameters and re-initiate the segmentation and rendering processes multiple times.
Innovation Solution
A computer system that obtains segmentation parameters based on user input and adjusts them dynamically through input device movements, allowing for interactive and real-time adjustment of segmentation parameters, thereby streamlining the image segmentation and rendering process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual parameter reconfiguration is performed to achieve satisfactory segmentation results, then segmentation accuracy is improved, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system implements real-time feedback by continuously monitoring user interactions with the 3D model and dynamically adjusting segmentation parameters based on this feedback. The processor detects user actions (such as rotating, zooming, or selecting regions) and automatically modifies segmentation settings to maintain or improve segmentation quality without requiring manual parameter adjustment, thus resolving the contradiction between accuracy and time consumption.
Solution Approach 2:
The segmentation system performs self-adjustment by automatically configuring and reconfiguring segmentation parameters based on user interactions with the visualized 3D model. The system serves itself by detecting when resegmentation is needed and autonomously adjusting parameters, eliminating the need for users to manually intervene in the parameter configuration process while maintaining high segmentation accuracy.
2Measurement precision
If multiple manual segmentation steps are performed to adjust parameters, then segmentation quality is improved, but ease of operation deteriorates
Solution Approach 1:
The system uses real-time feedback from user interactions with the 3D model to automatically adjust segmentation parameters. Instead of requiring users to manually configure multiple parameters step-by-step, the system detects user actions and autonomously modifies segmentation settings, thereby maintaining high segmentation quality while dramatically improving ease of operation.
Solution Approach 2:
The patent replaces the manual mechanical process of parameter adjustment with an automated computational system. The processor automatically detects user interactions and computes the appropriate parameter adjustments, substituting the manual mechanical operation with an intelligent automated system that maintains quality while improving ease of use.
3Measurement precision
If repeated segmentation and rendering processes are initiated, then satisfactory results are achieved, but device complexity and operational burden increase
Solution Approach 1:
The system maintains continuous useful action by seamlessly integrating segmentation parameter adjustment into the ongoing interaction flow. Instead of interrupting the user to perform separate configuration steps, the system continuously monitors interactions and dynamically adjusts parameters in real-time, maintaining process simplicity while achieving high-quality results through continuous adaptive segmentation.
Solution Approach 2:
The segmentation system transitions from a static, manual parameter configuration approach to a dynamic, adaptive system that automatically adjusts parameters based on real-time user interactions. This dynamic approach maintains satisfactory segmentation quality while reducing process complexity by eliminating the need for repeated manual reconfiguration cycles.
Data Source
AI summary
Methods and systems related to image segmentation are disclosed. In some examples, a computer system obtains segmentation parameters based on a selection of a region of a displayed image. The selection of the region is associated with a select signal generated by an input device. In response to obtaining the segmentation parameters, the computer system processes the image based on the segmentation parameters. The computer system further adjusts the segmentation parameters based on one or more move signals generated by the input device. The move signal is associated with moving of a representation of the input device within the image. The computer system processes the image based on the one or more adjusted segmentation parameters and displays an image of the selected region based on the processing of the image using the adjusted segmentation parameters.