dosma.models.IWOAIOAIUnet2DNormalized¶

class dosma.models.IWOAIOAIUnet2DNormalized(input_shape, weights_path, force_weights=False)[source]¶

Extension of model trained by Team 6 in the 2019 IWOAI Segmentation Challenge (with normalization).

This model uses the same architecture as IWOAIOAIUnet2D, but pre-processes the input data by zero-mean, unit-std normalization.

References

Desai, et al., “The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset.” arXiv preprint arXiv:2004.14003 (2020).

__init__(input_shape, weights_path, force_weights=False)¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`(input_shape, weights_path[, …])	Initialize self.
`build_model`(input_shape, weights_path)	Builds a segmentation model architecture and loads weights.
`generate_mask`(volume)	Segment the MRI volumes.

Attributes

`ALIASES`
`sigmoid_threshold`