Electrically tunable fluidic lens imaging system for laparoscopic fluorescence-guided surgery

Volpi, D; Tullis, Iain D. C.; Barber, Paul R.; Augustyniak, Edyta; Smart, Sean; Vallis, Katherine A.; Vojnovic, Borivoj

doi:10.1364/boe.8.003232

Cited by 23 publications

(17 citation statements)

References 31 publications

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“…The laparoscope had a light guide of 5 mm diameter bundle fiber connecting to the light source. Due to a focus shift that occurred when the wavelength was changed in the light source, the optical power of the tunable lens was set, as shown in Table 1, to adjust the focus [23]. By tuning the optical power, the angle of view changed on the order of several pixels.…”

Section: Light Source and Laparoscope For Otn-nir Multispectral Imagingmentioning

confidence: 99%

Over 1000 nm Near-Infrared Multispectral Imaging System for Laparoscopic In Vivo Imaging

Takamatsu

Kitagawa

Akimoto

et al. 2021

Sensors

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In this study, a laparoscopic imaging device and a light source able to select wavelengths by bandpass filters were developed to perform multispectral imaging (MSI) using over 1000 nm near-infrared (OTN-NIR) on regions under a laparoscope. Subsequently, MSI (wavelengths: 1000–1400 nm) was performed using the built device on nine live mice before and after tumor implantation. The normal and tumor pixels captured within the mice were used as teaching data sets, and the tumor-implanted mice data were classified using a neural network applied following a leave-one-out cross-validation procedure. The system provided a specificity of 89.5%, a sensitivity of 53.5%, and an accuracy of 87.8% for subcutaneous tumor discrimination. Aggregated true-positive (TP) pixels were confirmed in all tumor-implanted mice, which indicated that the laparoscopic OTN-NIR MSI could potentially be applied in vivo for classifying target lesions such as cancer in deep tissues.

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Section: Light Source and Laparoscope For Otn-nir Multispectral Imagingmentioning

confidence: 99%

Over 1000 nm Near-Infrared Multispectral Imaging System for Laparoscopic In Vivo Imaging

Takamatsu

Kitagawa

Akimoto

et al. 2021

Sensors

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“…In recent years, many groups have been working on this issue. In terms of hardware, various imaging systems have been developed for intraoperative FIGS, including systems designed for open and endoscopic surgeries, as well as systems utilizing NIR-II signals (optical spectrum: 1,000-1,700 nm) (46,(50)(51)(52)(53). Besides those effects, the improvement of software with new imaging algorithms can further mitigate the physical limitations in hardware systems.…”

Section: Figsmentioning

confidence: 99%

A review of the application of machine learning in molecular imaging

Yin¹,

Cao²,

Wang³

et al. 2021

Ann Transl Med

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Molecular imaging (MI) is a science that uses imaging methods to reflect the changes of molecular level in living state and conduct qualitative and quantitative studies on its biological behaviors in imaging. Optical molecular imaging (OMI) and nuclear medical imaging are two key research fields of MI.OMI technology refers to the optical information generated by the imaging target (such as tumors) due to drug intervention and other reasons. By collecting the optical information, researchers can track the motion trajectory of the imaging target at the molecular level. Owing to its high specificity and sensitivity, OMI has been widely used in preclinical research and clinical surgery. Nuclear medical imaging mainly detects ionizing radiation emitted by radioactive substances. It can provide molecular information for early diagnosis, effective treatment and basic research of diseases, which has become one of the frontiers and hot topics in the field of medicine in the world today. Both OMI and nuclear medical imaging technology require a lot of data processing and analysis. In recent years, artificial intelligence technology, especially neural networkbased machine learning (ML) technology, has been widely used in MI because of its powerful data processing capability. It provides a feasible strategy to deal with large and complex data for the requirement of MI. In this review, we will focus on the applications of ML methods in OMI and nuclear medical imaging.

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“…Possessing a shape-changing capability makes ETLs inherently prone to spherical aberrations, consequently limiting performance, and in turn image quality, in high-numerical-aperture (NA) applications. Some of these aberrations are beginning to be resolved through optoelectronic (Vogt, 2020) and computational (Cumming and Gu, 2020) solutions (see below for further details). Characterisation of the different aberrations that can arise while using an ETL has led to the proposal to use adaptive optics (AO) to reduce these errors (Fig.…”

Section: Challenges and Optimisation Of Etlsmentioning

confidence: 99%

Electrically tunable lenses – eliminating mechanical axial movements during high-speed 3D live imaging

Efstathiou

Draviam

2021

Journal of Cell Science

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The successful investigation of photosensitive and dynamic biological events, such as those in a proliferating tissue or a dividing cell, requires non-intervening high-speed imaging techniques. Electrically tunable lenses (ETLs) are liquid lenses possessing shape-changing capabilities that enable rapid axial shifts of the focal plane, in turn achieving acquisition speeds within the millisecond regime. These human-eye-inspired liquid lenses can enable fast focusing and have been applied in a variety of cell biology studies. Here, we review the history, opportunities and challenges underpinning the use of cost-effective high-speed ETLs. Although other, more expensive solutions for three-dimensional imaging in the millisecond regime are available, ETLs continue to be a powerful, yet inexpensive, contender for live-cell microscopy.

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Electrically tunable fluidic lens imaging system for laparoscopic fluorescence-guided surgery

Cited by 23 publications

References 31 publications

Over 1000 nm Near-Infrared Multispectral Imaging System for Laparoscopic In Vivo Imaging

Over 1000 nm Near-Infrared Multispectral Imaging System for Laparoscopic In Vivo Imaging

A review of the application of machine learning in molecular imaging

Electrically tunable lenses – eliminating mechanical axial movements during high-speed 3D live imaging

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