Head and neck cancer patient images for determining auto-segmentation accuracy in T2-weighted magnetic resonance imaging through expert manual segmentations.

ABSTRACT:

Purpose

The use of magnetic resonance imaging (MRI) in radiotherapy treatment planning has rapidly increased due to its ability to evaluate patient's anatomy without the use of ionizing radiation and due to its high soft tissue contrast. For these reasons, MRI has become the modality of choice for longitudinal and adaptive treatment studies. Automatic segmentation could offer many benefits for these studies. In this work, we describe a T2-weighted MRI dataset of head and neck cancer patients that can be used to evaluate the accuracy of head and neck normal tissue auto-segmentation systems through comparisons to available expert manual segmentations.

Acquisition and validation methods

T2-weighted MRI images were acquired for 55 head and neck cancer patients. These scans were

SUBMITTER: Cardenas CE 

PROVIDER: S-EPMC7322982 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature