Recovering Dense Tissue Multispectral Signal from in vivo RGB Images

Hyperspectral/multispectral imaging (HSI/MSI) contains rich information clinical applications, such as 1) narrow band imaging for vascular visualisation; 2) oxygen saturation for intraoperative perfusion monitoring and clinical decision making [1]; 3) tissue classification and identification of pathology [2]. The current systems which provide pixel-level HSI/MSI signal can be generally divided into two types: spatial scanning and spectral scanning. However, the trade-off between spatial/spectral resolution, the acquisition time, and the hardware complexity hampers implementation in real-world applications, especially intra-operatively. Acquiring high resolution images in real-time is important for HSI/MSI in intra-operative imaging, to alleviate the side effect caused by breathing, heartbeat, and other sources of motion. Therefore, we developed an algorithm to recover a pixel-level MSI stack using only the captured snapshot RGB images from a normal camera. We refer to this technique as "super-spectral-resolution". The proposed method enables recovery of pixel-level-dense MSI signals with 24 spectral bands at ~11 frames per second (FPS) on a GPU. Multispectral data captured from porcine bowel and sheep/rabbit uteri in vivo has been used for training, and the algorithm has been validated using unseen in vivo animal experiments.Comment: accepted by Hamlyn Symposium 201

Minimally-invasive surgical application of multispectral and polarization resolved imaging

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Noise, transient dynamics, and the generation of realistic interspike interval variation in square-wave burster neurons

First return maps of interspike intervals for biological neurons that generate repetitive bursts of impulses can display stereotyped structures (neuronal signatures). Such structures have been linked to the possibility of multicoding and multifunctionality in neural networks that produce and control rhythmical motor patterns. In some cases, isolating the neurons from their synaptic network revealsirregular, complex signatures that have been regarded as evidence of intrinsic, chaotic behavior. We show that incorporation of dynamical noise into minimal neuron models of square-wave bursting (either conductance-based or abstract) produces signatures akin to those observed in biological examples, without the need for fine-tuning of parameters or ad hoc constructions for inducing chaotic activity. The form of the stochastic term is not strongly constrained, and can approximate several possible sources of noise, e.g. random channel gating or synaptic bombardment. The cornerstone of this signature generation mechanism is the rich, transient, but deterministic dynamics inherent in the square-wave (saddle-node/homoclinic) mode of neuronal bursting. We show that noise causes the dynamics to populate a complex transient scaffolding or skeleton in state space, even for models that (without added noise) generate only periodic activity (whether in bursting or tonic spiking mode).Comment: REVTeX4-1, 18 pages, 9 figure

Maximising Achievable Rates of Experimental Nonlinear Optical Fibre Transmission Systems

It is generally expected that the demand for digital data services will continue to grow, placing ever greater requirements on optical fibre networks which carry the bulk of digital data. Research to maximise achievable information rates (AIR) over fibre has led to increasing spectral efficiency, symbol rate and bandwidth use. All of these contribute to transmission impairments due to the nonlinear nature of the optical fibre. This thesis describes research performed to investigate the effects of nonlinear impair- ments on the AIRs of experimental optical fibre transmission. To maximise throughput, the entire available optical bandwidth should be filled with transmission channels. An investigation into large bandwidth transmission through the use of spectrally shaped amplified spontaneous emission noise (SS-ASE) was con- ducted. The enhanced Gaussian noise model is used to analytically describe this tech- nique, and SS-ASE was experimentally shown to provide a lower bound on the AIR. Nonlinear interference (NLI) was modelled from an inter-symbol interference (ISI) model to characterise the noise and was experimentally verified. This new understand- ing helps quantify potential gain available from nonlinearity mitigation. Multicore fibres offer an alternative route to improve AIR, and are susceptible to another noise source known as crosstalk. This inter-core crosstalk can be controlled by suitable design of the fibre, hence in the limiting case, NLI rather than crosstalk will limit AIR. Nonlinearity compensation was, for the first time, experimentally demon- strated in the presence of crosstalk in a homogeneous 7-core fibre and shown to provide an increase in AIR. The results of this thesis can be used to evaluate future transmission systems for maximising information rates. It was shown that experimentally, SS-ASE is a viable transmission tool to evaluate system performance, NLI can be characterised using an ISI model and nonlinearity mitigation is possible in MCF systems limited by crosstalk

Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery

In surgical oncology, it is challenging for surgeons to identify lymph nodes and completely resect cancer even with pre-operative imaging systems like PET and CT, because of the lack of reliable intraoperative visualization tools. Endoscopic radio-guided cancer detection and resection has recently been evaluated whereby a novel tethered laparoscopic gamma detector is used to localize a preoperatively injected radiotracer. This can both enhance the endoscopic imaging and complement preoperative nuclear imaging data. However, gamma activity visualization is challenging to present to the operator because the probe is non-imaging and it does not visibly indicate the activity origination on the tissue surface. Initial failed attempts used segmentation or geometric methods, but led to the discovery that it could be resolved by leveraging high-dimensional image features and probe position information. To demonstrate the effectiveness of this solution, we designed and implemented a simple regression network that successfully addressed the problem. To further validate the proposed solution, we acquired and publicly released two datasets captured using a custom-designed, portable stereo laparoscope system. Through intensive experimentation, we demonstrated that our method can successfully and effectively detect the sensing area, establishing a new performance benchmark. Code and data are available at https://github.com/br0202/Sensing_area_detection.gitComment: Accepted by MICCAI 202

Fluorescence lifetime imaging microscopy: in vivo application to diagnosis of oral carcinoma

A compact clinically compatible fluorescence lifetime imaging microscopy (FLIM) system was designed and built for intraoperative disease diagnosis and validated in vivo in a hamster oral carcinogenesis model. This apparatus allows for the remote image collection via a flexible imaging probe consisting of a gradient index objective lens and a fiber bundle. Tissue autofluorescence (337 nm excitation) was imaged using an intensified CCD with a gate width down to 0.2 ns. We demonstrate a significant contrast in fluorescence lifetime between tumor (1.77±0.26 ns) and normal (2.50±0.36 ns) tissues at 450 nm and an over 80% intensity decrease at 390 nm emission in tumor versus normal areas. The time-resolved images were minimally affected by tissue morphology, endogenous absorbers, and illumination. These results demonstrate the potential of FLIM as an intraoperative diagnostic technique