Segmentation Models (dosma.models)

DOSMA currently supports pre-trained models for segmenting, each described in detail below. Model aliases are string fields used to distinguish/specify particular models in DOSMA (command-line argument --model).

All models are open-sourced under the GNU General Public License v3.0 license. If you use these models, please reference both DOSMA and the original work.

dosma.models.OAIUnet2D	Model trained in Chaudhari et al. IWOAI 2018.
dosma.models.IWOAIOAIUnet2D	Model trained by Team 6 in the 2019 IWOAI Segmentation Challenge.
dosma.models.IWOAIOAIUnet2DNormalized	Extension of model trained by Team 6 in the 2019 IWOAI Segmentation Challenge (with normalization).

OAI 2D U-Net

A 2D U-Net trained on a downsampled rendition of the OAI iMorphics DESS dataset [CFLH18]. Inputs are zero-mean, unit standard deviation normalized before segmentation.

Aliases: oai-unet2d, oai_unet2d

IWOAI Segmentation Challenge - Team 6 2D U-Net

This model was submitted by Team 6 to the 2019 International Workshop on Osteoarthritis Segmentation [DCI+20]. It consists of a 2D U-Net trained on the standardized OAI training dataset.

Note, inputs are not normalized before segmentation and therefore may be difficult to generalize to DESS scans with different parameters than the OAI.

Aliases: iwoai-2019-t6

IWOAI Segmentation Challenge - Team 6 2D U-Net (Normalized)

This model is a duplicate of the iwoai-2019-t6 network (above), but differs in that it uses zero-mean, unit standard deviation normalized inputs. This may make the network more robust to different DESS scan parameters and/or scanner vendors.

While this model was not submitted to the IWOAI challenge, the architecture, training parameters, and dataset are identical to the Team 6 submission. Performance on the standardized OAI test set was similar to the original network submitted by Team 6 (see table below).

Aliases: iwoai-2019-t6-normalized

Average (standard deviation) performance summary on OAI test set. Coefficient of variation is calculated as root-mean-square value.

	Femoral Cartilage	Tibial Cartilage	Patellar Cartilage	Meniscus
Dice	0.906 +/- 0.014	0.881 +/- 0.033	0.857 +/- 0.080	0.870 +/- 0.032
VOE	0.171 +/- 0.023	0.211 +/- 0.052	0.242 +/- 0.108	0.229 +/- 0.049
RMS-CV	0.019 +/- 0.011	0.048 +/- 0.029	0.076 +/- 0.061	0.045 +/- 0.025
ASSD (mm)	0.174 +/- 0.020	0.270 +/- 0.166	0.243 +/- 0.106	0.344 +/- 0.111