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Real-Time Interactive 3D Tumor Segmentation Using a Fast Level-Set Algorithm
Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. KTH Royal Institute Technology, Sweden; Sectra AB, S-58330 Linkoping, Sweden.ORCID-id: 0000-0002-0442-3524
Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.ORCID-id: 0000-0002-4111-1693
Region Östergötland, Diagnostikcentrum, Röntgenkliniken i Linköping. Linköpings universitet, Medicinska fakulteten. Linköpings universitet, Institutionen för medicin och hälsa, Avdelningen för radiologiska vetenskaper.
Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.ORCID-id: 0000-0002-9368-0177
Vise andre og tillknytning
2015 (engelsk)Inngår i: Journal of Medical Imaging and Health Informatics, ISSN 2156-7018, E-ISSN 2156-7026, Vol. 5, nr 8, s. 1998-2002Artikkel i tidsskrift (Fagfellevurdert) Published
Resurstyp
Text
Abstract [en]

A new level-set based interactive segmentation framework is introduced, where the algorithm learns the intensity distributions of the tumor and surrounding tissue from a line segment drawn by the user from the middle of the lesion towards the border. This information is used to design a likelihood function, which is then incorporated into the level-set framework as an external speed function guiding the segmentation. The endpoint of the input line segment sets a limit to the propagation of 3D region, i.e., when the zero-level-set crosses this point, the propagation is forced to stop. Finally, a fast level set algorithm with coherent propagation is used to solve the level set equation in real time. This allows the user to instantly see the 3D result while adjusting the position of the line segment to tune the parameters implicitly. The "fluctuating" character of the coherent propagation also enables the contour to coherently follow the mouse cursors motion when the user tries to fine-tune the position of the contour on the boundary, where the learned likelihood function may not necessarily change much. Preliminary results suggest that radiologists can easily learn how to use the proposed segmentation tool and perform relatively accurate segmentation with much less time than the conventional slice-by-slice based manual procedure.

sted, utgiver, år, opplag, sider
AMER SCIENTIFIC PUBLISHERS , 2015. Vol. 5, nr 8, s. 1998-2002
Emneord [en]
Interactive Image Segmentation; Level Set; Coherent Propagation; Tumor Segmentation
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-125166DOI: 10.1166/jmihi.2015.1685ISI: 000368564700072OAI: oai:DiVA.org:liu-125166DiVA, id: diva2:903382
Tilgjengelig fra: 2016-02-15 Laget: 2016-02-15 Sist oppdatert: 2018-01-10

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Wang, ChunliangDahlström, NilsFransson, Sven GöranLundström, ClaesSmedby, Örjan
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