Island Tool

It uses connected-component analysis to examine which pixels or voxels form contiguous groups. Each disconnected group can then be treated as a separate region rather than as part of one continuous segmentation. This mechanism lets the user identify isolated artifacts or segmentation errors and decide whether a group should remain in the anatomical or pathological representation.

The decision depends on whether the disconnected region belongs to the intended anatomical or pathological structure. A region that represents an artifact or segmentation error can be removed, while a meaningful disconnected structure can be retained. Separating these choices prevents automatic cleanup from discarding relevant findings and supports more accurate image-based interpretation.

Separating disconnected structures gives users finer control over the segmented image. Removing irrelevant islands reduces artifacts, whereas preserving selected regions maintains the structures needed for analysis. The resulting segmentation provides a cleaner representation of anatomy or disease, which can support more consistent measurements and improve the reliability of downstream three-dimensional modeling.

A typical workflow is to inspect the segmented image, identify disconnected pixel or voxel groups, and determine which groups are relevant to the target structure. The user then removes unwanted islands or retains selected regions before using the refined segmentation. This sequence corrects errors while preserving meaningful anatomical or pathological information.

The function is useful when a segmentation contains isolated regions that could interfere with later analysis. After refinement, the cleaned result can support image-based measurements, three-dimensional model generation, surgical planning, or radiotherapy workflows. Its value is greatest when unwanted islands would otherwise distort the representation used for interpretation or planning.

By helping users remove artifacts and correct segmentation errors, the tool produces a more reliable representation of the relevant anatomy or disease. That representation can then be used in surgical planning or radiotherapy workflows, where image-derived structures inform subsequent work. The tool therefore supports consistency in the imaging data underlying these medical applications.