Medical Detection Toolkit (Artificial Intelligence)

Medical Detection Toolkit (Artificial Intelligence)
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Uses : A comprehensive framework for object detection.

Features :

  • 2D + 3D implementations of prevalent object detectors
  • Modular and light-weight structure ensuring sharing of all processing steps (incl. backbone architecture) for comparability of models.
  • Training with bounding box and/or pixel-wise annotations.
  • Dynamic patching and tiling of 2D + 3D images (for training and inference)
  • Weighted consolidation of box predictions across patch-overlaps, ensembles, and dimensions.
  • Monitoring + evaluation simultaneously on object and patient level.
  • 2D + 3D output visualizations.
  • Integration of COCO mean average precision metric.
  • Integration of MIC-DKFZ batch generators for extensive data augmentation.
  • Easy modification to evaluation of instance segmentation and/or semantic segmentation.

Platform : Source code.

File formats :

Language/API : Python, PyTorch.

Documentation : Website.

Users : Advanced, Developer.

Access : Free, open source.

Links : https://github.com/MIC-DKFZ/medicaldetectiontoolkit

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