Tensor Decomposition for Colour Image Segmentation of Burn Wounds

Cirillo, Marco DomenicoLinköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten (author)

Funding Agencies|Faculty of Science and Engineering Grant
Research in burns has been a continuing demand over the past few decades, and important advancements are still needed to facilitate more effective patient stabilization and reduce mortality rate. Burn wound assessment, which is an important task for surgical management, largely depends on the accuracy of burn area and burn depth estimates. Automated quantification of these burn parameters plays an essential role for reducing these estimate errors conventionally carried out by clinicians. The task for automated burn area calculation is known as image segmentation. In this paper, a new segmentation method for burn wound images is proposed. The proposed methods utilizes a method of tensor decomposition of colour images, based on which effective texture features can be extracted for classification. Experimental results showed that the proposed method outperforms other methods not only in terms of segmentation accuracy but also computational speed.

Mirdell, RobinLinköpings universitet,Avdelningen för Kirurgi, Ortopedi och Onkologi,Medicinska fakulteten,Region Östergötland, Hand- och plastikkirurgiska kliniken US(Swepub:liu)robmi25 (author)
Sjöberg, FolkeLinköpings universitet,Avdelningen för Kirurgi, Ortopedi och Onkologi,Medicinska fakulteten,Region Östergötland, Hand- och plastikkirurgiska kliniken US(Swepub:liu)folsj94 (author)
Pham, TuanLinköpings universitet,Avdelningen för medicinsk teknik,Tekniska fakulteten(Swepub:liu)tuaph15 (author)
Linköpings universitetAvdelningen för medicinsk teknik (creator_code:org_t)

By the author/editor: Cirillo, Marco D ...; Mirdell, Robin; Sjöberg, Folke; Pham, Tuan

About the subject

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Medical Engineer ...; and Medical Image Pr ...

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