Wavelet Subspace Analysis of Intraoperative Thermal Imaging for Motion Filtering

Hoffmann, Nico; Hollmach, Julia; Schnabel, Christian; Radev, Yordan; Kirsch, Matthias; Petersohn, Uwe; Koch, Edmund; Steiner, Gerald

doi:10.1007/978-3-319-11755-3_46

Cited by 6 publications

(1 citation statement)

References 9 publications

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“…Kateb et al (2009) used Intraoperative Thermal Imaging (ITI) in a patient with a metastatic intracortical melanoma and showed that ITI is a novel neuroimaging technique that can potentially locate the margins of primary and metastatic brain tumors. Hollmach et al (2013), Hoffmann et al (2014) and Kastek et al (2014) investigated the applicability and accuracy of the intraoperative thermography in the neurosurgical procedures.…”

Section: Introductionmentioning

confidence: 99%

Finite element modeling of haptic thermography: A novel approach for brain tumor detection during minimally invasive neurosurgery

Sadeghi-Goughari

Mojra

2015

Journal of Thermal Biology

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Section: Introductionmentioning

confidence: 99%

Finite element modeling of haptic thermography: A novel approach for brain tumor detection during minimally invasive neurosurgery

Sadeghi-Goughari

Mojra

2015

Journal of Thermal Biology

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A robust motion correction technique for infrared thermography during awake craniotomy

2023

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Purpose Intraoperative infrared thermography is an emerging technique for image-guided neurosurgery, whereby physiological and pathological processes result in temperature changes over space and time. However, motion during data collection leads to downstream artifacts in thermography analyses. We develop a fast, robust technique for motion estimation and correction as a preprocessing step for brain surface thermography recordings. Methods A motion correction technique for thermography was developed which approximates the deformation field associated with motion as a grid of two-dimensional bilinear splines (Bispline registration), and a regularization function was designed to constrain motion to biomechanically feasible solutions. The performance of the proposed Bispline registration technique was compared to phase correlation, a band-stop filter, demons registration, and the Horn–Schunck and Lucas–Kanade optical flow techniques. Results All methods were analyzed using thermography data from ten patients undergoing awake craniotomy for brain tumor resection, and performance was compared using image quality metrics. The proposed method had the lowest mean-squared error and the highest peak-signal-to-noise ratio of all methods tested and performed slightly worse than phase correlation and Demons registration on the structural similarity index metric (p < 0.01, Wilcoxon signed-rank test). Band-stop filtering and the Lucas–Kanade method were not strong attenuators of motion, while the Horn–Schunck method was well-performing initially but weakened over time. Conclusion Bispline registration had the most consistently strong performance out of all the techniques tested. It is relatively fast for a nonrigid motion correction technique, capable of processing ten frames per second, and could be a viable option for real-time use. Constraining the deformation cost function through regularization and interpolation appears sufficient for fast, monomodal motion correction of thermal data during awake craniotomy.

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Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

Sadeghi-Goughari¹,

Mojra²,

Sadeghi³

2016

J. Phys. D: Appl. Phys.

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Wavelet Subspace Analysis of Intraoperative Thermal Imaging for Motion Filtering

Cited by 6 publications

References 9 publications

Finite element modeling of haptic thermography: A novel approach for brain tumor detection during minimally invasive neurosurgery

Finite element modeling of haptic thermography: A novel approach for brain tumor detection during minimally invasive neurosurgery

A robust motion correction technique for infrared thermography during awake craniotomy

Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

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