Deblurring Multispectral Laparoscopic Images

Jones, Geoffrey; Clancy, Neil T.; Arridge, Simon; Elson, Daniel S.; Stoyanov, Danail

doi:10.1007/978-3-319-07521-1_23

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…Given assumptions that individual band measurements are each across a narrow spectral range, without overlapping each other and that there is no fluorescence and negligible constant scattering, estimating chromophore concentrations becomes a linear fitting problem. While having a large number of spectral bands enables good fitting results, it often comes at the cost of the reduced temporal resolution of acquiring the whole multispectral cube, making it difficult to image tissue intra-operatively due to physiological motion [16], [17], [18], [19]. Filter wheel and strobe illumination can allow for rapid data acquisition, while LCTF approaches typically provide more fine spectral data.…”

Section: Related Work In Msi For Surgerymentioning

confidence: 99%

Bayesian Estimation of Intrinsic Tissue Oxygenation and Perfusion From RGB Images

Jones

Clancy²,

Helo

et al. 2017

IEEE Trans. Med. Imaging

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Multispectral imaging (MSI) can potentially assist the intra-operative assessment of tissue structure, function and viability, by providing information about oxygenation. In this paper, we present a novel technique for recovering intrinsic MSI measurements from endoscopic RGB images without custom hardware adaptations. The advantage of this approach is that it requires no modification to existing surgical and diagnostic endoscopic imaging systems. Our method uses a radiometric color calibration of the endoscopic camera's sensor in conjunction with a Bayesian framework to recover a per-pixel measurement of the total blood volume (THb) and oxygen saturation (SO) in the observed tissue. The sensor's pixel measurements are modeled as weighted sums over a mixture of Poisson distributions and we optimize the variables SO and THb to maximize the likelihood of the observations. To validate our technique, we use synthetic images generated from Monte Carlo physics simulation of light transport through soft tissue containing sub-surface blood vessels. We also validate our method on in vivo data by comparing it to a MSI dataset acquired with a hardware system that sequentially images multiple spectral bands without overlap. Our results are promising and show that we are able to provide surgeons with additional relevant information by processing endoscopic images with our modeling and inference framework.

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Section: Related Work In Msi For Surgerymentioning

confidence: 99%

Bayesian Estimation of Intrinsic Tissue Oxygenation and Perfusion From RGB Images

Jones

Clancy²,

Helo

et al. 2017

IEEE Trans. Med. Imaging

Self Cite

View full text Add to dashboard Cite

show abstract

One step surgical scene restoration for robot assisted minimally invasive surgery

Ali

Jonmohamadi

Fontanarosa

et al. 2023

Sci Rep

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Minimally invasive surgery (MIS) offers several advantages to patients including minimum blood loss and quick recovery time. However, lack of tactile or haptic feedback and poor visualization of the surgical site often result in some unintentional tissue damage. Visualization aspects further limits the collection of imaged frame contextual details, therefore the utility of computational methods such as tracking of tissue and tools, scene segmentation, and depth estimation are of paramount interest. Here, we discuss an online preprocessing framework that overcomes routinely encountered visualization challenges associated with the MIS. We resolve three pivotal surgical scene reconstruction tasks in a single step; namely, (i) denoise, (ii) deblur, and (iii) color correction. Our proposed method provides a latent clean and sharp image in the standard RGB color space from its noisy, blurred, and raw inputs in a single preprocessing step (end-to-end in one step). The proposed approach is compared against current state-of-the-art methods that perform each of the image restoration tasks separately. Results from knee arthroscopy show that our method outperforms existing solutions in tackling high-level vision tasks at a significantly reduced computation time.

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Deblurring Multispectral Laparoscopic Images

Cited by 2 publications

References 16 publications

Bayesian Estimation of Intrinsic Tissue Oxygenation and Perfusion From RGB Images

Bayesian Estimation of Intrinsic Tissue Oxygenation and Perfusion From RGB Images

One step surgical scene restoration for robot assisted minimally invasive surgery

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