CerebNet.datasets.utils¶
- class CerebNet.datasets.utils.LTADict[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
()
- CerebNet.datasets.utils.bounding_volume_offset(img, target_img_size, image_shape=None)[source]¶
Find the center of the non-zero values in img and returns offsets so this center is in the center of a bounding volume of size target_img_size.
- CerebNet.datasets.utils.filter_blank_slices_thick(data_dict, threshold=10)[source]¶
Function to filter blank slices from the volume using the label volume :param dict data_dict: dictionary containing all volumes need to be filtered :return:
- CerebNet.datasets.utils.map_label2subseg(mapped_subseg, label_type='cereb_subseg')[source]¶
Function to perform look-up table mapping from label space to subseg space