Automatic Sternum Segmentation in Thoracic MRI

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Dias, M (Author) Other; Rocha, B (Author) Other; João Teixeira (Author) FEUP; Oliveira, HP (Author) FCUP

Conference proceedings International

Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Pages: 1018-1021

41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019

23 July 2019 through 27 July 2019

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 3 Citations

Other information

Authenticus ID: P-00R-MMV

DOI: 10.1109/embc.2019.8857860

Abstract (EN): The Sternum is a human bone located in the anterior area of the thoracic cage. It is present in most of the axial cuts provided from the Magnetic Resonance Imaging (MRI) acquisitions. used in the medical field. Detecting the Sternum is relevant as it contains rigid key-points for 3D model reconstructions, assisting in the planning and evaluation of several surgical procedures, and for atlas development by segmenting structures in anatomical proximity. In the absence of applicable approaches for this specific problem. this paper focuses on two distinct automated methods for Sternum segmentation in MRI. The first. relies on K-Means (Clustering) to perform the segmentation, while the second encompasses the closed Minimum Path over the elliptical transformation of Gradient images. A dataset of 14 annotated acquisitions was used for evaluation. The results favored the Gradient approach over Clustering.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4