CerebNet.data_loader.dataset¶

class CerebNet.data_loader.dataset.CerebDataset(dataset_path, cfg, transforms, load_aux_data)[source]¶

Class for loading aseg file with augmentations (transforms)

Methods

get_subject_names

class CerebNet.data_loader.dataset.LocalizerROI[source]¶

Methods

`clear`()
`copy`()
`fromkeys`(iterable[, value])	Create a new dictionary with keys from iterable and values set to value.
`get`(key[, default])	Return the value for key if key is in the dictionary, else default.
`items`()
`keys`()
`pop`(key[, default])	If the key is not found, return the default if given; otherwise, raise a KeyError.
`popitem`(/)	Remove and return a (key, value) pair as a 2-tuple.
`setdefault`(key[, default])	Insert key with a value of default if key is not in the dictionary.
`update`([E, ]**F)	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
`values`()

class CerebNet.data_loader.dataset.SubjectDataset(img_org, brain_seg, patch_size, slice_thickness, primary_slice=None)[source]¶

Single subject loader to load and prepare slices for network process.

Attributes

Returns the active plane

Methods

`locate_mask_bbox`(mask)	Find the largest connected component of the mask.
`set_plane`(plane)	Set the active plane.

locate_mask_bbox(mask)[source]¶

Find the largest connected component of the mask.

Parameters:

Returns:

tuple of 6 ints: Bounding box the cerebellum 6 coordinates: x_min, y_min, z_min, x_max, y_max, z_max.

class CerebNet.data_loader.dataset.TestLoader(subject_path, data_cfg, transforms=None)[source]¶

Methods