Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain

Gerald Zwettler; Robert Pichler; Werner Backfrieder

doi:10.1007/978-3-642-27579-1_27

Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain

Gerald Zwettler, Robert Pichler, Werner Backfrieder

Research Center Hagenberg

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

Abstract

Accurate diagnostic assessment of metabolic processes in nuclear medicine diagnostic imaging, e.g. SPECT and PET, rely on specific localization of physiological activity. The major step in precise staging of neuro-degenerative diseases is robust, patient-specific classification of the brain. In this work a vascularization-based classification strategy for MRI datasets of the brain is introduced to handle variability of patient's anatomy. The vascularization-based classification utilizes skeletonization in combination with m-adjacency to construct a hierarchical vessel tree from binary pre-segmentations. Based on the vessel topology, the brain voxels are classified with respect to a minimal distance criterion from the vessel branches they are assigned to. This blood-supply oriented approach shows proper segmentation of respective anatomical regions of the human brain. Results are validated on T1-weighted brainweb database.

Original language	English
Title of host publication	Computer Aided Systems Theory, EUROCAST 2011 - 13th International Conference, Revised Selected Papers
Pages	209-216
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-27579-1_27
Publication status	Published - 2012
Event	13th International Conference on Computer Aided Systems Theory, Eurocast 2011 - Las Palmas de Gran Canaria, Spain Duration: 6 Feb 2011 → 11 Feb 2011 http://www.iuctc.ulpgc.es/spain/eurocast2011/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6928 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Computer Aided Systems Theory, Eurocast 2011
Country/Territory	Spain
City	Las Palmas de Gran Canaria
Period	06.02.2011 → 11.02.2011
Internet address	http://www.iuctc.ulpgc.es/spain/eurocast2011/

Keywords

morphological classification
skeletonization
vessel tree modeling

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-642-27579-1_27

Cite this

Zwettler, G., Pichler, R., & Backfrieder, W. (2012). Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain. In Computer Aided Systems Theory, EUROCAST 2011 - 13th International Conference, Revised Selected Papers (PART 2 ed., pp. 209-216). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6928 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-27579-1_27

Zwettler, Gerald ; Pichler, Robert ; Backfrieder, Werner. / Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain. Computer Aided Systems Theory, EUROCAST 2011 - 13th International Conference, Revised Selected Papers. PART 2. ed. 2012. pp. 209-216 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "Accurate diagnostic assessment of metabolic processes in nuclear medicine diagnostic imaging, e.g. SPECT and PET, rely on specific localization of physiological activity. The major step in precise staging of neuro-degenerative diseases is robust, patient-specific classification of the brain. In this work a vascularization-based classification strategy for MRI datasets of the brain is introduced to handle variability of patient's anatomy. The vascularization-based classification utilizes skeletonization in combination with m-adjacency to construct a hierarchical vessel tree from binary pre-segmentations. Based on the vessel topology, the brain voxels are classified with respect to a minimal distance criterion from the vessel branches they are assigned to. This blood-supply oriented approach shows proper segmentation of respective anatomical regions of the human brain. Results are validated on T1-weighted brainweb database.",

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Zwettler, G, Pichler, R & Backfrieder, W 2012, Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain. in Computer Aided Systems Theory, EUROCAST 2011 - 13th International Conference, Revised Selected Papers. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6928 LNCS, pp. 209-216, 13th International Conference on Computer Aided Systems Theory, Eurocast 2011, Las Palmas de Gran Canaria, Spain, 06.02.2011. https://doi.org/10.1007/978-3-642-27579-1_27

Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain. / Zwettler, Gerald; Pichler, Robert; Backfrieder, Werner.
Computer Aided Systems Theory, EUROCAST 2011 - 13th International Conference, Revised Selected Papers. PART 2. ed. 2012. p. 209-216 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6928 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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AB - Accurate diagnostic assessment of metabolic processes in nuclear medicine diagnostic imaging, e.g. SPECT and PET, rely on specific localization of physiological activity. The major step in precise staging of neuro-degenerative diseases is robust, patient-specific classification of the brain. In this work a vascularization-based classification strategy for MRI datasets of the brain is introduced to handle variability of patient's anatomy. The vascularization-based classification utilizes skeletonization in combination with m-adjacency to construct a hierarchical vessel tree from binary pre-segmentations. Based on the vessel topology, the brain voxels are classified with respect to a minimal distance criterion from the vessel branches they are assigned to. This blood-supply oriented approach shows proper segmentation of respective anatomical regions of the human brain. Results are validated on T1-weighted brainweb database.

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Zwettler G, Pichler R, Backfrieder W. Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain. In Computer Aided Systems Theory, EUROCAST 2011 - 13th International Conference, Revised Selected Papers. PART 2 ed. 2012. p. 209-216. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-27579-1_27

Diagnosis of neurodegenerative diseases based on multi-modal hemodynamic classification of the brain

Abstract

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Keywords

UN SDGs

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