medmask.core.segmask
core.segmask
Classes
| Name | Description |
|---|---|
| SegmentationMask | Represents a 3-D segmentation mask with semantic labels. |
SegmentationMask
core.segmask.SegmentationMask(mask_array, mapping, space=None)Represents a 3-D segmentation mask with semantic labels.
A segmentation mask is a 3-D ndarray whose voxel values represent integer labels (e.g. 0=background, 1=liver, 2=spleen …). This class stores the mask array itself together with its :class:~spacetransformer.core.space.Space (geometry) and a bi-directional mapping between names (“liver”) and labels (1).
The mask array is always stored in (z,y,x) format internally, ensuring consistent behavior for Python users.
There are two ways to build a mask instance:
- Complete initialisation – provide a full ndarray and a mapping.
- Lazy initialisation – create an empty mask of the desired bit-depth first via :meth:
lazy_init, then add label regions incrementally with :meth:add_label.
Attributes
| Name | Description |
|---|---|
| bit_depth | Bit-depth of the underlying array (1 / 8 / 16 / 32). |
| data | Return mask data array as read-only view in (z,y,x) format. |
Methods
| Name | Description |
|---|---|
| add_label | Paint a mask region with label and register name. |
| lazy_init | Create an empty mask with given bit-depth. |
| load | Load a mask from path (.msk) and return a new SegmentationMask. |
| save | Save this mask to path using the storage layer (MaskFile). |
| to_binary | Return a boolean array where non-zero voxels are True. |
add_label
core.segmask.SegmentationMask.add_label(mask, label, name)Paint a mask region with label and register name.
mask must be a boolean ndarray of the same shape as this mask.
lazy_init
core.segmask.SegmentationMask.lazy_init(bit_depth, *, space=None, shape=None)Create an empty mask with given bit-depth.
Either space or shape must be supplied to infer the array dimensions. The resulting mask array will be in (z,y,x) format.
load
core.segmask.SegmentationMask.load(path)Load a mask from path (.msk) and return a new SegmentationMask.
save
core.segmask.SegmentationMask.save(path, *, codec=None)Save this mask to path using the storage layer (MaskFile).
to_binary
core.segmask.SegmentationMask.to_binary()Return a boolean array where non-zero voxels are True.