Literature DB >> 17081729

Extraocular muscle quantification using mathematical morphology: a semi-automatic method for analyzing muscle enlargement in orbital diseases.

André Domingos Araújo Souza1, Evandro Eduardo Seron Ruiz, Antonio Augusto Velasco Cruz.   

Abstract

Mathematical morphology was used to quantify the dimensions of the human extraocular muscles in computed tomography orbital scans. Coronal images of 28 patients with Graves orbitopathy and 5 controls (218 orbital scans) were analyzed with an algorithm for extraocular muscle segmentation. The results showed that measurements of extraocular muscle area obtained with semi-automatic segmentation are highly correlated with manual tracing and provides a simple method to quantify orbital structures including the extraocular muscles.

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Year:  2006        PMID: 17081729     DOI: 10.1016/j.compmedimag.2006.09.010

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  3 in total

1.  Quantitative analysis of orbital soft tissues on computed tomography to assess the activity of thyroid-associated orbitopathy.

Authors:  Jun Soo Byun; Nam Ju Moon; Jeong Kyu Lee
Journal:  Graefes Arch Clin Exp Ophthalmol       Date:  2016-11-12       Impact factor: 3.117

2.  Monitoring and Predicting Treatment Response of Extraocular Muscles in Grave's Orbitopathy by 99mTc-DTPA SPECT/CT.

Authors:  Chengzhi Jiang; Zilong Deng; Jin Huang; Haoyu Deng; Jia Tan; Xinhui Li; Min Zhao
Journal:  Front Med (Lausanne)       Date:  2021-12-16

3.  Neural network-based method for diagnosis and severity assessment of Graves' orbitopathy using orbital computed tomography.

Authors:  Jaesung Lee; Wangduk Seo; Jaegyun Park; Won-Seon Lim; Ja Young Oh; Nam Ju Moon; Jeong Kyu Lee
Journal:  Sci Rep       Date:  2022-07-15       Impact factor: 4.996

  3 in total

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