Dr. Andrea Visentin Profile

Dr. Andrea Visentin

at Univ College Cork

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SPIE Journal Paper | 5 September 2023 Open Access

Frameworks of wavelength selection in diffuse reflectance spectroscopy for tissue differentiation in orthopedic surgery

Celina Li, Carl Fisher, Katarzyna Komolibus, Konstantin Grygoryev, Huihui Lu, Ray Burke, Andrea Visentin, Stefan Andersson-Engels

JBO, Vol. 28, Issue 12, 121207, (September 2023) https://doi.org/10.1117/12.10.1117/1.JBO.28.12.121207

KEYWORDS: Bone, Tissues, Principal component analysis, Cements, Diffuse reflectance spectroscopy, Surgery, Data modeling, Education and training, Feature selection, Absorption

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SignificanceWavelength selection from a large diffuse reflectance spectroscopy (DRS) dataset enables removal of spectral multicollinearity and thus leads to improved understanding of the feature domain. Feature selection (FS) frameworks are essential to discover the optimal wavelengths for tissue differentiation in DRS-based measurements, which can facilitate the development of compact multispectral optical systems with suitable illumination wavelengths for clinical translation.AimThe aim was to develop an FS methodology to determine wavelengths with optimal discriminative power for orthopedic applications, while providing the frameworks for adaptation to other clinical scenarios.ApproachAn ensemble framework for FS was developed, validated, and compared with frameworks incorporating conventional algorithms, including principal component analysis (PCA), linear discriminant analysis (LDA), and backward interval partial least squares (biPLS).ResultsVia the one-versus-rest binary classification approach, a feature subset of 10 wavelengths was selected from each framework yielding comparable balanced accuracy scores (PCA: 94.8 ± 3.47 % , LDA: 98.2 ± 2.02 % , biPLS: 95.8 ± 3.04 % , and ensemble: 95.8 ± 3.16 % ) to those of using all features (100%) for cortical bone versus the rest class labels. One hundred percent balanced accuracy scores were generated for bone cement versus the rest. Different feature subsets achieving similar outcomes could be identified due to spectral multicollinearity.ConclusionsWavelength selection frameworks provide a means to explore domain knowledge and discover important contributors to classification in spectroscopy. The ensemble framework generated a model with improved interpretability and preserved physical interpretation, which serves as the basis to determine illumination wavelengths in optical instrumentation design.

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