Graphical Protocol Builder for Biological Image Analysis
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Solution Overview
Problem
Current image analysis protocols in drug discovery and biological research lack flexibility and user-friendly capabilities, particularly for cell-based assays, as they require programming knowledge and are limited in defining complex relationships between interrelated image objects.
Innovation Solution
A computer-based method for developing image analysis protocols that allows users to select and define target identification settings, relationships between image objects, and measurements, enabling the creation of complex hierarchies and user-defined calculations without programming expertise, using a graphical user interface for automated image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-defined canned image analysis protocols are used, then the system is easy to operate, but the protocol flexibility and adaptability are limited
Solution Approach 1:
The system dynamically adapts between two operational modes: a simplified mode for ease of operation using pre-configured protocols, and a flexible mode allowing users to dynamically define custom protocols through a graphical interface. This dynamic switching resolves the contradiction by providing both simplicity and adaptability depending on user needs.
Solution Approach 2:
The image analysis system is designed to perform multiple functions: it can execute both pre-defined canned protocols for simple operations and user-customized protocols for complex, adaptable scenarios. This multi-functionality allows the same system to serve both ease of operation and protocol flexibility requirements.
2Ease of operation
If canned image analysis protocols are used with parameter variation, then the ease of operation is maintained, but the ability to define complex relationships between interrelated objects is limited
Solution Approach 1:
The system introduces an intermediary graphical protocol development environment that mediates between simple parameter adjustment and complex relationship definition. This intermediary layer allows users to visually construct complex relationships between interrelated objects without requiring programming knowledge, thus maintaining ease of operation while enhancing adaptability.
Solution Approach 2:
The system replaces the mechanical approach of parameter variation within fixed protocols with a visual programming interface that allows dynamic construction of analysis workflows. This substitution enables complex relationship definitions through graphical manipulation rather than constrained parameter adjustment.
3Device complexity
If feature gates with range limits are used to define object subsets, then the protocol development is simplified, but the flexibility in defining image processing protocols remains limited
Solution Approach 1:
The system segments the protocol development process into distinct visual components and building blocks that can be independently configured and combined. This segmentation allows complex protocols to be constructed from simpler modular elements, reducing overall complexity while maintaining flexibility.
Solution Approach 2:
The protocol development system transitions from static feature gates with fixed range limits to a dynamic visual programming environment where protocol structures can be flexibly modified. This dynamic approach allows users to adapt protocol definitions to specific experimental needs without being constrained by pre-defined gate structures.
4Ease of operation
If users without programming background are to develop custom protocols, then the ease of operation must be improved, but previously programming knowledge was required for flexible protocol development
Solution Approach 1:
The system replaces programming-based protocol development with a graphical user interface that uses visual drag-and-drop operations and point-and-click configuration. This substitution eliminates the need for programming knowledge while maintaining full custom protocol development capability, thus improving ease of operation without sacrificing adaptability.
Solution Approach 2:
The graphical protocol development environment acts as an intermediary that translates user-friendly visual operations into complex image analysis protocols. This intermediary layer shields users from programming complexity while enabling them to develop customized protocols with full flexibility.
Data Source
AI summary
A computer-based method for the development of an image analysis protocol for analyzing image data, the image data containing images including image objects, in particular biological image objects such as biological cells. The image analysis protocol, once developed, is operable in an image analysis software system to report on one or more measurements conducted on selected ones of the image objects. The development process includes providing functions for selecting predetermined image analysis procedures, the functions allowing the user to define:at least one first target identification setting for identifying a first target set of image objects in the image data;at least one second target identification setting for identifying a second target set of image objects in the image data;a relationship between the first and second set of image objects; andone or more measurements which are to be reported for the image data, the measurements being conducted using the defined relationship.