Background and activities
About Asgeir Bjørgan
Primarily working on real-time processing of hyperspectral images, with applications to medical diagnostics.
Scientific, academic and artistic work
Displaying a selection of activities. See all publications in the database
- (2016) Spectral-spatial classification combined with diffusion theory based inverse modeling of hyperspectral images. Progress in Biomedical Optics and Imaging. vol. 9689.
- (2016) Can spectral-spatial image segmentation be used to discriminate experimental burn wounds?. Journal of Biomedical Optics. vol. 21:101413 (10).
- (2015) Vessel contrast enhancement in hyperspectral images. Progress in Biomedical Optics and Imaging. vol. 9318:93180G.
- (2015) Real-time noise removal for line-scanning hyperspectral devices using a minimum noise fraction-based approach. Sensors. vol. 15 (2).
- (2015) Towards real-time medical diagnostics using hyperspectral imaging technology. Progress in Biomedical Optics and Imaging. vol. 9537.
- (2015) Hyperspectral imaging for detection of cholesterol in human skin. Progress in Biomedical Optics and Imaging. vol. 93320.
- (2014) Estimation of skin optical parameters for real-time hyperspectral imaging applications. Journal of Biomedical Optics. vol. 19 (6).
- (2014) Wavelet based feature extraction and visualization in hyperspectral tissue characterization. Biomedical Optics Express. vol. 5 (12).
- (2014) Identification of inflammation sites in arthritic joints using hyperspectral imaging. Proceedings of SPIE, the International Society for Optical Engineering. vol. 8947.
- (2016) A physics-informed characterization of burn wound segmentation maps obtained from hyperspectral images. Norwegian Electro Optics Meeting 2016 ; Voss. 2016-04-13 - 2016-04-15.
- (2015) Line-by-line denoising of hyperspectral images using a minimum noise fraction-based approach - C++ source code, available on https://github.com/ntnu-bioopt/mnf. NTNU. 2015.
- (2015) gpudm: Estimation of skin optical parameters from hyperspectral images using CUDA. C++/CUDA source code, available on https://github.com/ntnu-bioopt/gpudm. NTNU. 2015.