AnatomySketch

AnatomySketch provides a platform for medical image segmentation and algorithm development to support annotation, model training, data visualization, and clinical validation of medical image analysis algorithms.

Key Features:

• Extensible Plugin Interface: A plugin architecture allows integration of custom algorithm modules for prototyping and testing within the platform.
• Model Training: Supports model training workflows for deep learning-based segmentation algorithms.
• Data Visualization: Provides data visualization capabilities for inspecting medical images and algorithm outputs.
• Advanced Annotation Tools: Offers annotation tools for precise image labeling to generate training data for segmentation models.
• Human-AI Collaboration: Enables human-in-the-loop collaboration between expert annotators and AI algorithms to refine segmentation results.
• Annotation-by-Iterative-Deep-Learning (AID): Supports the AID workflow for iterative annotation and model refinement.
• Clinical Validation Support: Supports clinical validation by enabling creation of software prototypes for testing in clinical contexts.

Scientific Applications:

• Customized MRI Image Diagnosis: Facilitates tailored diagnostic workflows for MRI by integrating user-defined algorithms.
• Interactive Lung Lobe Segmentation: Supports interactive lung lobe segmentation with real-time adjustments to improve accuracy.
• Human-AI Collaborated Spine Disc Segmentation: Combines human expertise and AI to improve precision in spine disc segmentation tasks.
• Annotation-by-Iterative-Deep-Learning (AID): Enables iterative training processes for deep learning models using AID to optimize performance.

Methodology:

Uses a plugin-based architecture to integrate custom algorithm modules, supports model training and data visualization, provides annotation tools and Annotation-by-Iterative-Deep-Learning (AID) for iterative training, and enables human-in-the-loop collaboration for segmentation refinement.