Automated Extraction of Anatomical Measurements From Temporal Bone CT Imaging

Authors

Andy S Ding
Alexander Lu
Zhaoshuo Li
Deepa Galaiya
Masaru Ishii
Jeffrey H Siewerdsen
Russell H Taylor
Francis X Creighton

Publication Date

10-1-2022

Journal

Otolaryngology–Head and Neck Surgery

Abstract

OBJECTIVE: Proposed methods of minimally invasive and robot-assisted procedures within the temporal bone require measurements of surgically relevant distances and angles, which often require time-consuming manual segmentation of preoperative imaging. This study aims to describe an automatic segmentation and measurement extraction pipeline of temporal bone cone-beam computed tomography (CT) scans.

STUDY DESIGN: Descriptive study of temporal bone measurements.

SETTING: Academic institution.

METHODS: A propagation template composed of 16 temporal bone CT scans was formed with relevant anatomical structures and landmarks manually segmented. Next, 52 temporal bone CT scans were autonomously segmented using deformable registration techniques from the Advanced Normalization Tools Python package. Anatomical measurements were extracted via in-house Python algorithms. Extracted measurements were compared to ground truth values from manual segmentations.

RESULTS: Paired

CONCLUSIONS: This is the first study to automatically extract relevant temporal bone anatomical measurements from CT scans using segmentation propagation. Measurements from these models can streamline preoperative planning, improve future segmentation techniques, and help develop future image-guided or robot-assisted systems for temporal bone procedures.

Keywords

Algorithms, Cone-Beam Computed Tomography, Facial Nerve, Humans, Image Processing, Computer-Assisted, Temporal Bone, Tomography, X-Ray Computed

Comments

PMID: 35133916