Publications by authors named "Sami Puustinen"

The dataset consists of 101 hyperspectral images of four human placentas and six hyperspectral images of contrast dyes (i.e., indocyanine green and red and blue food colorant) that were captured in the range 515-900 nm, step = 5 nm.

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Background: Hyperspectral imaging (HSI) has the potential to enhance surgical tissue detection and diagnostics. Definite utilization of intraoperative HSI guidance demands validated machine learning and public datasets that currently do not exist. Moreover, current imaging conventions are dispersed, and evidence-based paradigms for neurosurgical HSI have not been declared.

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Background: 5-aminolevulinic acid (5-ALA) - precursor of protoporphyrin IX (PpIX) - is utilized in fluorescence guided surgery (FGS) of high-grade gliomas. PpIX is used to identify traces of glioma during resection. Visual inspection of the fluorescence seems inaccurate in comparison to optic techniques such as hyperspectral imaging (HSI).

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Article Synopsis
  • Distinct tissue types can be identified using narrow-band imaging (NBI) during surgery, but previous studies often overlooked the impact of various factors like lighting and microstructural changes on image analysis.
  • The study involved capturing images of facial nerves and internal carotid arteries from temporal bones and analyzing them with a custom spectral imaging system, which highlighted differences in reflectance among different tissue types.
  • The results showed that the U-Net algorithm accurately classified over 90% of pixels, suggesting that NBI could be a valuable tool for improving tissue identification in surgical settings, although more research is needed for effective clinical use.
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