Dynamic multiatlas selection-based consensus segmentation of head and neck structures from CT images.

ABSTRACT:

Purpose

Manual delineation of head and neck (H&N) organ-at-risk (OAR) structures for radiation therapy planning is time consuming and highly variable. Therefore, we developed a dynamic multiatlas selection-based approach for fast and reproducible segmentation.

Methods

Our approach dynamically selects and weights the appropriate number of atlases for weighted label fusion and generates segmentations and consensus maps indicating voxel-wise agreement between different atlases. Atlases were selected for a target as those exceeding an alignment weight called dynamic atlas attention index. Alignment weights were computed at the image level and called global weighted voting (GWV) or at the structure level and called structure weighted voting (SWV) by using a normalized metric comp

SUBMITTER: Haq R 

PROVIDER: S-EPMC7042892 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature