Inference of tissue haemoglobin concentration from Stereo RGB

Multispectral imaging (MSI) can provide information about tissue oxygenation, perfusion and potentially function during surgery. In this paper we present a novel, near real-time technique for intrinsic measurements of total haemoglobin (THb) and blood oxygenation (SO 22 ) in tissue using only RGB images from a stereo laparoscope. The high degree of spectral overlap between channels makes inference of haemoglobin concentration challenging, non-linear and under constrained. We decompose the problem into two constrained linear sub-problems and show that with Tikhonov regularisation the estimation significantly improves, giving robust estimation of the THb. We demonstrate by using the co-registered stereo image data from two cameras it is possible to get robust SO 22 estimation as well. Our method is closed from, providing computational efficiency even with multiple cameras. The method we present requires only spectral response calibration of each camera, without modification of existing laparoscopic imaging hardware. We validate our technique on synthetic data from Monte Carlo simulation and further, in vivo, on a multispectral porcine data set

Computational Multispectral Endoscopy

Minimal Access Surgery (MAS) is increasingly regarded as the de-facto approach in interventional medicine for conducting many procedures this is due to the reduced patient trauma and consequently reduced recovery times, complications and costs. However, there are many challenges in MAS that come as a result of viewing the surgical site through an endoscope and interacting with tissue remotely via tools, such as lack of haptic feedback; limited field of view; and variation in imaging hardware. As such, it is important best utilise the imaging data available to provide a clinician with rich data corresponding to the surgical site. Measuring tissue haemoglobin concentrations can give vital information, such as perfusion assessment after transplantation; visualisation of the health of blood supply to organ; and to detect ischaemia. In the area of transplant and bypass procedures measurements of the tissue tissue perfusion/total haemoglobin (THb) and oxygen saturation (SO2) are used as indicators of organ viability, these measurements are often acquired at multiple discrete points across the tissue using with a specialist probe. To acquire measurements across the whole surface of an organ one can use a specialist camera to perform multispectral imaging (MSI), which optically acquires sequential spectrally band limited images of the same scene. This data can be processed to provide maps of the THb and SO2 variation across the tissue surface which could be useful for intra operative evaluation. When capturing MSI data, a trade off often has to be made between spectral sensitivity and capture speed. The work in thesis first explores post processing blurry MSI data from long exposure imaging devices. It is of interest to be able to use these MSI data because the large number of spectral bands that can be captured, the long capture times, however, limit the potential real time uses for clinicians. Recognising the importance to clinicians of real-time data, the main body of this thesis develops methods around estimating oxy- and deoxy-haemoglobin concentrations in tissue using only monocular and stereo RGB imaging data

Bayesian Estimation of Intrinsic Tissue Oxygenation and Perfusion from RGB Images

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 colour 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 (SO2) in the observed tissue. The sensor's pixel measurements are modelled as weighted sums over a mixture of Poisson distributions and we optimise the variables SO2 and THb to maximise the likelihood of the observations. To validate our technique, we use synthetic images generated from Monte Carlo (MC) 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 modelling and inference framework

Characterization of color cross-talk of CCD detectors and its influence in multispectral quantitative phase imaging

Multi-spectral quantitative phase imaging (QPI) is an emerging imaging modality for wavelength dependent studies of several biological and industrial specimens. Simultaneous multi-spectral QPI is generally performed with color CCD cameras. However, color CCD cameras are suffered from the color crosstalk issue, which needed to be explored. Here, we present a new approach for accurately measuring the color crosstalk of 2D area detectors, without needing prior information about camera specifications. Color crosstalk of two different cameras commonly used in QPI, single chip CCD (1-CCD) and three chip CCD (3-CCD), is systematically studied and compared using compact interference microscopy. The influence of color crosstalk on the fringe width and the visibility of the monochromatic constituents corresponding to three color channels of white light interferogram are studied both through simulations and experiments. It is observed that presence of color crosstalk changes the fringe width and visibility over the imaging field of view. This leads to an unwanted non-uniform background error in the multi-spectral phase imaging of the specimens. It is demonstrated that the color crosstalk of the detector is the key limiting factor for phase measurement accuracy of simultaneous multi-spectral QPI systems.Comment: 16 pages, 8 figure

Multispectral image analysis in laparoscopy – A machine learning approach to live perfusion monitoring

Modern visceral surgery is often performed through small incisions. Compared to open surgery, these minimally invasive interventions result in smaller scars, fewer complications and a quicker recovery. While to the patients benefit, it has the drawback of limiting the physician’s perception largely to that of visual feedback through a camera mounted on a rod lens: the laparoscope. Conventional laparoscopes are limited by “imitating” the human eye. Multispectral cameras remove this arbitrary restriction of recording only red, green and blue colors. Instead, they capture many specific bands of light. Although these could help characterize important indications such as ischemia and early stage adenoma, the lack of powerful digital image processing prevents realizing the technique’s full potential. The primary objective of this thesis was to pioneer fluent functional multispectral imaging (MSI) in laparoscopy. The main technical obstacles were: (1) The lack of image analysis concepts that provide both high accuracy and speed. (2) Multispectral image recording is slow, typically ranging from seconds to minutes. (3) Obtaining a quantitative ground truth for the measurements is hard or even impossible. To overcome these hurdles and enable functional laparoscopy, for the first time in this field physical models are combined with powerful machine learning techniques. The physical model is employed to create highly accurate simulations, which in turn teach the algorithm to rapidly relate multispectral pixels to underlying functional changes. To reduce the domain shift introduced by learning from simulations, a novel transfer learning approach automatically adapts generic simulations to match almost arbitrary recordings of visceral tissue. In combination with the only available video-rate capable multispectral sensor, the method pioneers fluent perfusion monitoring with MSI. This system was carefully tested in a multistage process, involving in silico quantitative evaluations, tissue phantoms and a porcine study. Clinical applicability was ensured through in-patient recordings in the context of partial nephrectomy; in these, the novel system characterized ischemia live during the intervention. Verified against a fluorescence reference, the results indicate that fluent, non-invasive ischemia detection and monitoring is now possible. In conclusion, this thesis presents the first multispectral laparoscope capable of videorate functional analysis. The system was successfully evaluated in in-patient trials, and future work should be directed towards evaluation of the system in a larger study. Due to the broad applicability and the large potential clinical benefit of the presented functional estimation approach, I am confident the descendants of this system are an integral part of the next generation OR

Visual Tracking in Robotic Minimally Invasive Surgery

Intra-operative imaging and robotics are some of the technologies driving forward better and more effective minimally invasive surgical procedures. To advance surgical practice and capabilities further, one of the key requirements for computationally enhanced interventions is to know how instruments and tissues move during the operation. While endoscopic video captures motion, the complex appearance dynamic effects of surgical scenes are challenging for computer vision algorithms to handle with robustness. Tackling both tissue and instrument motion estimation, this thesis proposes a combined non-rigid surface deformation estimation method to track tissue surfaces robustly and in conditions with poor illumination. For instrument tracking, a keypoint based 2D tracker that relies on the Generalized Hough Transform is developed to initialize a 3D tracker in order to robustly track surgical instruments through long sequences that contain complex motions. To handle appearance changes and occlusion a patch-based adaptive weighting with segmentation and scale tracking framework is developed. It takes a tracking-by-detection approach and a segmentation model is used to assigns weights to template patches in order to suppress back- ground information. The performance of the method is thoroughly evaluated showing that without any offline-training, the tracker works well even in complex environments. Finally, the thesis proposes a novel 2D articulated instrument pose estimation framework, which includes detection-regression fully convolutional network and a multiple instrument parsing component. The framework achieves compelling performance and illustrates interesting properties includ- ing transfer between different instrument types and between ex vivo and in vivo data. In summary, the thesis advances the state-of-the art in visual tracking for surgical applications for both tissue and instrument motion estimation. It contributes to developing the technological capability of full surgical scene understanding from endoscopic video

Development of an image guidance system for laparoscopic liver surgery and evaluation of optical and computer vision techniques for the assessment of liver tissue

Introduction: Liver resection is increasingly being carried out via the laparoscopic approach (keyhole surgery) because there is mounting evidence that it benefits patients by reducing pain and length of hospitalisation. There are however ongoing concerns about oncological radicality (i.e. ability to completely remove cancer) and an inability to control massive haemorrhage. These issues can partially be attributed to a loss of sensation such as depth perception, tactile feedback and a reduced field of view. Utilisation of optical imaging and computer vision may be able to compensate for some of the lost sensory input because these modalities can facilitate visualisation of liver tissue and structural anatomy. Their use in laparoscopy is attractive because it is easy to adapt or integrate with existing technology. The aim of this thesis is to explore to what extent this technology can aid in the detection of normal and abnormal liver tissue and structures. / Methods: The current state of the art for optical imaging and computer vision in laparoscopic liver surgery is assessed in a systematic review. Evaluation of confocal laser endomicroscopy is carried out on a murine and porcine model of liver disease. Multispectral near infrared imaging is evaluated on ex-vivo liver specimen. Video magnification is assessed on a mechanical flow phantom and a porcine model of liver disease. The latter model was also employed to develop a computer vision based image guidance system for laparoscopic liver surgery. This image guidance system is further evaluated in a clinical feasibility study. Where appropriate, experimental findings are substantiated with statistical analysis. / Results: Use of confocal laser endomicroscopy enabled discrimination between cancer and normal liver tissue with a sub-millimetre precision. This technology also made it possible to verify the adequacy of thermal liver ablation. Multispectral imaging, at specific wavelengths was shown to have the potential to highlight the presence of colorectal and hepatocellular cancer. An image reprocessing algorithm is proposed to simplify visual interpretation of the resulting images. It is shown that video magnification can determine the presence of pulsatile motion but that it cannot reliably determine the extent of motion. Development and performance metrics of an image guidance system for laparoscopic liver surgery are outlined. The system was found to improve intraoperative orientation more development work is however required to enable reliable prediction of oncological margins. / Discussion: The results in this thesis indicate that confocal laser endomicroscopy and image guidance systems have reached a development stage where their intraoperative use may benefit surgeons by visualising features of liver anatomy and tissue characteristics. Video magnification and multispectral imaging require more development and suggestions are made to direct this work. It is also highlighted that it is crucial to standardise assessment methods for these technologies which will allow a more direct comparison between the outcomes of different groups. Limited imaging depth is a major restriction of these technologies but this may be overcome by combining them with preoperatively obtained imaging data. Just like laparoscopy, optical imaging and computer vision use functions of light, a shared characteristic that makes their combined use complementary

Multimodal optical systems for clinical oncology

This thesis presents three multimodal optical (light-based) systems designed to improve the capabilities of existing optical modalities for cancer diagnostics and theranostics. Optical diagnostic and therapeutic modalities have seen tremendous success in improving the detection, monitoring, and treatment of cancer. For example, optical spectroscopies can accurately distinguish between healthy and diseased tissues, fluorescence imaging can light up tumours for surgical guidance, and laser systems can treat many epithelial cancers. However, despite these advances, prognoses for many cancers remain poor, positive margin rates following resection remain high, and visual inspection and palpation remain crucial for tumour detection. The synergistic combination of multiple optical modalities, as presented here, offers a promising solution. The first multimodal optical system (Chapter 3) combines Raman spectroscopic diagnostics with photodynamic therapy using a custom-built multimodal optical probe. Crucially, this system demonstrates the feasibility of nanoparticle-free theranostics, which could simplify the clinical translation of cancer theranostic systems without sacrificing diagnostic or therapeutic benefit. The second system (Chapter 4) applies computer vision to Raman spectroscopic diagnostics to achieve spatial spectroscopic diagnostics. It provides an augmented reality display of the surgical field-of-view, overlaying spatially co-registered spectroscopic diagnoses onto imaging data. This enables the translation of Raman spectroscopy from a 1D technique to a 2D diagnostic modality and overcomes the trade-off between diagnostic accuracy and field-of-view that has limited optical systems to date. The final system (Chapter 5) integrates fluorescence imaging and Raman spectroscopy for fluorescence-guided spatial spectroscopic diagnostics. This facilitates macroscopic tumour identification to guide accurate spectroscopic margin delineation, enabling the spectroscopic examination of suspicious lesions across large tissue areas. Together, these multimodal optical systems demonstrate that the integration of multiple optical modalities has potential to improve patient outcomes through enhanced tumour detection and precision-targeted therapies.Open Acces

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio