hybrid-cs-model-mri#
Use Case and High-Level Description#
The hybrid-cs-model-mri
model is a hybrid frequency-domain/image-domain deep network for Magnetic Resonance Image (MRI) reconstruction. The model is composed of a k-space network that essentially tries to fill missing k-space samples, an Inverse Discrete Fourier Transformation (IDFT) operation, and an image-domain network that acts as an anti-aliasing filter.
More details provided in the paper and repository.
Specification#
Metric |
Value |
---|---|
Type |
MRI Image Inpainting in k-Space |
GFlops |
146.6037 |
MParams |
11.3313 |
Source framework |
TensorFlow* |
Accuracy#
Accuracy metrics are obtained on Calgary-Campinas Public Brain MR Dataset.
Metric |
Value |
---|---|
PSNR (mean) |
34.272884 dB |
PSNR (std) |
4.607115 dB |
Use accuracy_check [...] --model_attributes <path_to_folder_with_downloaded_model>
to specify the path to additional model attributes. path_to_folder_with_downloaded_model
is a path to the folder, where the current model is downloaded by Model Downloader tool.
Input#
Original model#
MRI input, name - input_1
, shape - 1, 256, 256, 2
, format - B, H, W, C
, where:
B
- batch sizeH
- image heightW
- image widthC
- number of channels
Converted model#
MRI input, name - input_1
, shape - 1, 256, 256, 2
, format - B, H, W, C
, where:
B
- batch sizeH
- image heightW
- image widthC
- number of channels
Output#
Original model#
The net outputs a blob with the name StatefulPartitionedCall/model/conv2d_43/BiasAdd/Add
and shape 1, 1, 256, 256
, containing reconstructed MR image.
Converted model#
The net outputs a blob with the name StatefulPartitionedCall/model/conv2d_43/BiasAdd/Add
and shape 1, 1, 256, 256
, containing reconstructed MR image.
Download a Model and Convert it into OpenVINO™ IR Format#
You can download models and if necessary convert them into OpenVINO™ IR format using the Model Downloader and other automation tools as shown in the examples below.
An example of using the Model Downloader:
omz_downloader --name <model_name>
An example of using the Model Converter:
omz_converter --name <model_name>
Demo usage#
The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:
Legal Information#
The original model is distributed under the following license:
MIT License
Copyright (c) 2018 Roberto M Souza
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.