Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images

Cheimariotis Grigorios-Aris; Mariam Al-Mashat; Haris Kostas; Aletras H. Anthony; Jonas Jögi; Marika Bajc; Maglaveras Nicolaos; Einar Heiberg

doi:10.1109/EMBC.2016.7590940

Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images

Cheimariotis Grigorios-Aris, Mariam Al-Mashat, Haris Kostas, Aletras H. Anthony, Jonas Jögi, Marika Bajc, Maglaveras Nicolaos, Einar Heiberg

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

Sammanfattning

This paper presents a fully automated method for segmentation of 3D SPECT ventilation and perfusion images. It relies on statistical information on lung shape derived by CT manual segmentation and its main processing steps are: shape model extraction, binary segmentation, positioning of mean shape in SPECT images and iterative shape adaptation based on intensity profiles and on what is considered 'plausible' lung shape. The Active Shape Model is used to generate accurate anatomic results in SPECT images with functional information and thus unclear borders, especially in the case of pathologies. The method was compared against ground truth manual segmentation on CT images, using volumetric, difference dice coefficient, sensitivity and precision.

Originalspråk	engelska
Titel på värdpublikation	2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Förlag	IEEE - Institute of Electrical and Electronics Engineers Inc.
Sidor	1280-1283
Antal sidor	4
Volym	2016-October
ISBN (elektroniskt)	9781457702204
DOI	https://doi.org/10.1109/EMBC.2016.7590940
Status	Published - 2016 okt. 13
Evenemang	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, USA Varaktighet: 2016 aug. 16 → 2016 aug. 20

Konferens

Konferens	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Land/Territorium	USA
Ort	Orlando
Period	2016/08/16 → 2016/08/20

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Grigorios-Aris, C., Al-Mashat, M., Kostas, H., Anthony, A. H., Jögi, J., Bajc, M., Nicolaos, M., & Heiberg, E. (2016). Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images. I 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 (Vol. 2016-October, s. 1280-1283). Artikel 7590940 IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2016.7590940

Grigorios-Aris, Cheimariotis ; Al-Mashat, Mariam ; Kostas, Haris et al. / Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Vol. 2016-October IEEE - Institute of Electrical and Electronics Engineers Inc., 2016. s. 1280-1283

@inproceedings{e9a3bce2b7744b478f1e18a3b290acc6,

title = "Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images",

abstract = "This paper presents a fully automated method for segmentation of 3D SPECT ventilation and perfusion images. It relies on statistical information on lung shape derived by CT manual segmentation and its main processing steps are: shape model extraction, binary segmentation, positioning of mean shape in SPECT images and iterative shape adaptation based on intensity profiles and on what is considered 'plausible' lung shape. The Active Shape Model is used to generate accurate anatomic results in SPECT images with functional information and thus unclear borders, especially in the case of pathologies. The method was compared against ground truth manual segmentation on CT images, using volumetric, difference dice coefficient, sensitivity and precision.",

author = "Cheimariotis Grigorios-Aris and Mariam Al-Mashat and Haris Kostas and Anthony, {Aletras H.} and Jonas J{\"o}gi and Marika Bajc and Maglaveras Nicolaos and Einar Heiberg",

year = "2016",

month = oct,

day = "13",

doi = "10.1109/EMBC.2016.7590940",

language = "English",

volume = "2016-October",

pages = "1280--1283",

booktitle = "2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 ; Conference date: 16-08-2016 Through 20-08-2016",

}

Grigorios-Aris, C, Al-Mashat, M, Kostas, H, Anthony, AH, Jögi, J , Bajc, M, Nicolaos, M & Heiberg, E 2016, Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images. i 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. vol. 2016-October, 7590940, IEEE - Institute of Electrical and Electronics Engineers Inc., s. 1280-1283, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016, Orlando, USA, 2016/08/16. https://doi.org/10.1109/EMBC.2016.7590940

Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images. / Grigorios-Aris, Cheimariotis; Al-Mashat, Mariam; Kostas, Haris et al.
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Vol. 2016-October IEEE - Institute of Electrical and Electronics Engineers Inc., 2016. s. 1280-1283 7590940.

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

TY - GEN

T1 - Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images

AU - Grigorios-Aris, Cheimariotis

AU - Al-Mashat, Mariam

AU - Kostas, Haris

AU - Anthony, Aletras H.

AU - Jögi, Jonas

AU - Bajc, Marika

AU - Nicolaos, Maglaveras

AU - Heiberg, Einar

PY - 2016/10/13

Y1 - 2016/10/13

N2 - This paper presents a fully automated method for segmentation of 3D SPECT ventilation and perfusion images. It relies on statistical information on lung shape derived by CT manual segmentation and its main processing steps are: shape model extraction, binary segmentation, positioning of mean shape in SPECT images and iterative shape adaptation based on intensity profiles and on what is considered 'plausible' lung shape. The Active Shape Model is used to generate accurate anatomic results in SPECT images with functional information and thus unclear borders, especially in the case of pathologies. The method was compared against ground truth manual segmentation on CT images, using volumetric, difference dice coefficient, sensitivity and precision.

AB - This paper presents a fully automated method for segmentation of 3D SPECT ventilation and perfusion images. It relies on statistical information on lung shape derived by CT manual segmentation and its main processing steps are: shape model extraction, binary segmentation, positioning of mean shape in SPECT images and iterative shape adaptation based on intensity profiles and on what is considered 'plausible' lung shape. The Active Shape Model is used to generate accurate anatomic results in SPECT images with functional information and thus unclear borders, especially in the case of pathologies. The method was compared against ground truth manual segmentation on CT images, using volumetric, difference dice coefficient, sensitivity and precision.

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BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016

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Grigorios-Aris C, Al-Mashat M, Kostas H, Anthony AH, Jögi J , Bajc M et al. Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images. I 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. Vol. 2016-October. IEEE - Institute of Electrical and Electronics Engineers Inc. 2016. s. 1280-1283. 7590940 doi: 10.1109/EMBC.2016.7590940

Automatic segmentation of lungs in SPECT images using active shape model trained by meshes delineated in CT images

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