... | ... | @@ -4,7 +4,7 @@ Given a family of objects, the atlas model proposes to learn a **template shape* |
|
|
|
|
|
The figure below describes the deterministic atlas model.
|
|
|
|
|
|
## Filling the xml files
|
|
|
## A toy example
|
|
|
|
|
|
We need to configure the three different xml files: `model.xml`, `data_set.xml`, `optimization_parameters.xml`. We follow here the `examples/atlas/landmark/2d/skulls` example.
|
|
|
|
... | ... | @@ -62,7 +62,7 @@ This file contains the paths to all the objects. Each observation is a **subject |
|
|
|
|
|
It is kept at a minimum for this example, and simply indicates the **optimization-method-type**, the **max-iterations** number and the use of a Sobolev gradient (use to obtain a smoother template).
|
|
|
|
|
|
## Running the example
|
|
|
### Running the example
|
|
|
|
|
|
The example can be run using the command:
|
|
|
|
... | ... | @@ -75,6 +75,6 @@ This will run the estimation and save output in the output folder. In this outpu |
|
|
- The set of momenta used, in txt format. Each paragraph of this file is the set of momenta used for one subject. They can be used to perform statistical tasks on a population.
|
|
|
- The residuals of the fit: the list of distances between the targets and the reconstructed objects.
|
|
|
|
|
|
## Pre-processing
|
|
|
## A note on pre-processing
|
|
|
|
|
|
In general, we advise to have the shapes rigidly aligned before running an atlas. It is also advised to use a relevant initialization for the initial template shape e.g. using one of the observations. |