Variational approach to semi-automated 2D image segmentation

Jaromír Kukal; Zuzana Krbcová; Iva Nachtigalová; Jan Švihlík; Karel Fliegel

doi:10.1117/12.2529374

6 September 2019 Variational approach to semi-automated 2D image segmentation

Jaromír Kukal, Zuzana Krbcová, Iva Nachtigalová, Jan Švihlík, Karel Fliegel

Proceedings Volume 11137, Applications of Digital Image Processing XLII; 111372H (2019) https://doi.org/10.1117/12.2529374
Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States

Abstract

The segmentation of 2D biomedical images is very complex problem which has to be solved interactively. Original MRI, CT, PET, or SPECT image can be enhanced using variational smoother. However, there are Regions of Interest (ROI) which can be exactly localized. The question is how to design human interaction with computer for user friendly biomedical service. Our approach is based on user selected points which determine the ROI border line. The relationship between point positions and image intensity is subject of variational interpolation using thin plate spline model. The general principle of segmentation is demonstrated on biomedical images of human brain.

Citation Download Citation

Jaromír Kukal, Zuzana Krbcová, Iva Nachtigalová, Jan Švihlík, and Karel Fliegel "Variational approach to semi-automated 2D image segmentation", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 111372H (6 September 2019); https://doi.org/10.1117/12.2529374

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