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Pregled bibliografske jedinice broj: 701773

Segmentation of Hepatic Vessels from Mri Images for Planning of Electroporation-Based Treatments in the Liver


Marčan, Marija; Pavliha, Denis; Musić, Marolt Maja; Fučkan, Igor; Magjarević, Ratko; Miklavčić, Damijan
Segmentation of Hepatic Vessels from Mri Images for Planning of Electroporation-Based Treatments in the Liver // Radiology and oncology, 1 (2014), 1; 1-15 doi:10.2478/raon-2014-0022 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 701773 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Segmentation of Hepatic Vessels from Mri Images for Planning of Electroporation-Based Treatments in the Liver

Autori
Marčan, Marija ; Pavliha, Denis ; Musić, Marolt Maja ; Fučkan, Igor ; Magjarević, Ratko ; Miklavčić, Damijan

Izvornik
Radiology and oncology (1318-2099) 1 (2014), 1; 1-15

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
electrochemotherapy ; non-thermal irreversible electroporation ; treatment planning ; hepatic vessel segmentation ; non-invasive tumor treatments ; MRI of liver

Sažetak
Introduction. Electroporation-based treatments rely on increasing the permeability of the cell membrane by high voltage electric pulses delivered to tissue via electrodes. To ensure that the whole tumor is covered by the sufficiently high electric field, accurate numerical models are built based on individual patient geometry. For the purpose of reconstruction of hepatic vessels from MRI images we searched for an optimal segmentation method that would meet the following initial criteria: identify major hepatic vessels, be robust and work with minimal user input. Materials and methods. We tested the approaches based on vessel enhancement filtering, thresholding, and their combination in local thresholding. The methods were evaluated on a phantom and clinical data. Results. Results show that thresholding based on variance minimization provides less error than the one based on entropy maximization. Best results were achieved by performing local thresholding of the original de-biased image in the regions of interest which were determined through previous vessel-enhancement filtering. In evaluation on clinical cases the proposed method scored in average sensitivity of 93.68%, average symmetric surface distance of 0.89 mm and Hausdorff distance of 4.04 mm. Conclusions. The proposed method to segment hepatic vessels from MRI images based on local thresholding meets all the initial criteria set at the beginning of the study and necessary to be used in treatment planning of electroporation- based treatments: it identifies the major vessels, provides results with consistent accuracy and works completely automatically. Whether the achieved accuracy is acceptable or not for treatment planning models remains to be verified through numerical modeling of effects of the segmentation error on the distribution of the electric field.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekti:
036-0362979-1554 - Neinvazivna mjerenja i postupci u biomedicini (Tonković, Stanko, MZO ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Ratko Magjarević (autor)

Poveznice na cjeloviti tekst rada:

doi www.ncbi.nlm.nih.gov

Citiraj ovu publikaciju:

Marčan, Marija; Pavliha, Denis; Musić, Marolt Maja; Fučkan, Igor; Magjarević, Ratko; Miklavčić, Damijan
Segmentation of Hepatic Vessels from Mri Images for Planning of Electroporation-Based Treatments in the Liver // Radiology and oncology, 1 (2014), 1; 1-15 doi:10.2478/raon-2014-0022 (međunarodna recenzija, članak, znanstveni)
Marčan, M., Pavliha, D., Musić, M., Fučkan, I., Magjarević, R. & Miklavčić, D. (2014) Segmentation of Hepatic Vessels from Mri Images for Planning of Electroporation-Based Treatments in the Liver. Radiology and oncology, 1 (1), 1-15 doi:10.2478/raon-2014-0022.
@article{article, author = {Mar\v{c}an, Marija and Pavliha, Denis and Musi\'{c}, Marolt Maja and Fu\v{c}kan, Igor and Magjarevi\'{c}, Ratko and Miklav\v{c}i\'{c}, Damijan}, year = {2014}, pages = {1-15}, DOI = {10.2478/raon-2014-0022}, keywords = {electrochemotherapy, non-thermal irreversible electroporation, treatment planning, hepatic vessel segmentation, non-invasive tumor treatments, MRI of liver}, journal = {Radiology and oncology}, doi = {10.2478/raon-2014-0022}, volume = {1}, number = {1}, issn = {1318-2099}, title = {Segmentation of Hepatic Vessels from Mri Images for Planning of Electroporation-Based Treatments in the Liver}, keyword = {electrochemotherapy, non-thermal irreversible electroporation, treatment planning, hepatic vessel segmentation, non-invasive tumor treatments, MRI of liver} }
@article{article, author = {Mar\v{c}an, Marija and Pavliha, Denis and Musi\'{c}, Marolt Maja and Fu\v{c}kan, Igor and Magjarevi\'{c}, Ratko and Miklav\v{c}i\'{c}, Damijan}, year = {2014}, pages = {1-15}, DOI = {10.2478/raon-2014-0022}, keywords = {electrochemotherapy, non-thermal irreversible electroporation, treatment planning, hepatic vessel segmentation, non-invasive tumor treatments, MRI of liver}, journal = {Radiology and oncology}, doi = {10.2478/raon-2014-0022}, volume = {1}, number = {1}, issn = {1318-2099}, title = {Segmentation of Hepatic Vessels from Mri Images for Planning of Electroporation-Based Treatments in the Liver}, keyword = {electrochemotherapy, non-thermal irreversible electroporation, treatment planning, hepatic vessel segmentation, non-invasive tumor treatments, MRI of liver} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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