172 research outputs found

    Retrieval and Registration of Long-Range Overlapping Frames for Scalable Mosaicking of In Vivo Fetoscopy

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    Purpose: The standard clinical treatment of Twin-to-Twin Transfusion Syndrome consists in the photo-coagulation of undesired anastomoses located on the placenta which are responsible to a blood transfer between the two twins. While being the standard of care procedure, fetoscopy suffers from a limited field-of-view of the placenta resulting in missed anastomoses. To facilitate the task of the clinician, building a global map of the placenta providing a larger overview of the vascular network is highly desired. Methods: To overcome the challenging visual conditions inherent to in vivo sequences (low contrast, obstructions or presence of artifacts, among others), we propose the following contributions: (i) robust pairwise registration is achieved by aligning the orientation of the image gradients, and (ii) difficulties regarding long-range consistency (e.g. due to the presence of outliers) is tackled via a bag-of-word strategy, which identifies overlapping frames of the sequence to be registered regardless of their respective location in time. Results: In addition to visual difficulties, in vivo sequences are characterised by the intrinsic absence of gold standard. We present mosaics motivating qualitatively our methodological choices and demonstrating their promising aspect. We also demonstrate semi-quantitatively, via visual inspection of registration results, the efficacy of our registration approach in comparison to two standard baselines. Conclusion: This paper proposes the first approach for the construction of mosaics of placenta in in vivo fetoscopy sequences. Robustness to visual challenges during registration and long-range temporal consistency are proposed, offering first positive results on in vivo data for which standard mosaicking techniques are not applicable.Comment: Accepted for publication in International Journal of Computer Assisted Radiology and Surgery (IJCARS

    FetReg2021: A Challenge on Placental Vessel Segmentation and Registration in Fetoscopy

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    Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomoses to regulate blood exchange among twins. The procedure is particularly challenging due to the limited field of view, poor manoeuvrability of the fetoscope, poor visibility, and variability in illumination. These challenges may lead to increased surgery time and incomplete ablation. Computer-assisted intervention (CAI) can provide surgeons with decision support and context awareness by identifying key structures in the scene and expanding the fetoscopic field of view through video mosaicking. Research in this domain has been hampered by the lack of high-quality data to design, develop and test CAI algorithms. Through the Fetoscopic Placental Vessel Segmentation and Registration (FetReg2021) challenge, which was organized as part of the MICCAI2021 Endoscopic Vision challenge, we released the first largescale multicentre TTTS dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms. For this challenge, we released a dataset of 2060 images, pixel-annotated for vessels, tool, fetus and background classes, from 18 in-vivo TTTS fetoscopy procedures and 18 short video clips. Seven teams participated in this challenge and their model performance was assessed on an unseen test dataset of 658 pixel-annotated images from 6 fetoscopic procedures and 6 short clips. The challenge provided an opportunity for creating generalized solutions for fetoscopic scene understanding and mosaicking. In this paper, we present the findings of the FetReg2021 challenge alongside reporting a detailed literature review for CAI in TTTS fetoscopy. Through this challenge, its analysis and the release of multi-centre fetoscopic data, we provide a benchmark for future research in this field

    Contribution of type W human endogenous retroviruses to the human genome: Characterization of HERV-W proviral insertions and processed pseudogenes

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    Background: Human endogenous retroviruses (HERVs) are ancient sequences integrated in the germ line cells and vertically transmitted through the offspring constituting about 8% of our genome. In time, HERVs accumulated mutations that compromised their coding capacity. A prominent exception is HERV-W locus 7q21.2, producing a functional Env protein (Syncytin-1) coopted for placental syncytiotrophoblast formation. While expression of HERV-W sequences has been investigated for their correlation to disease, an exhaustive description of the group composition and characteristics is still not available and current HERV-W group information derive from studies published a few years ago that, of course, used the rough assemblies of the human genome available at that time. This hampers the comparison and correlation with current human genome assemblies. Results: In the present work we identified and described in detail the distribution and genetic composition of 213 HERV-W elements. The bioinformatics analysis led to the characterization of several previously unreported features and provided a phylogenetic classification of two main subgroups with different age and structural characteristics. New facts on HERV-W genomic context of insertion and co-localization with sequences putatively involved in disease development are also reported. Conclusions: The present work is a detailed overview of the HERV-W contribution to the human genome and provides a robust genetic background useful to clarify HERV-W role in pathologies with poorly understood etiology, representing, to our knowledge, the most complete and exhaustive HERV-W dataset up to date

    High Data Output and Automated 3D Correlative Light–Electron Microscopy Method

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    Correlative light/electron microscopy (CLEM) allows the simultaneous observation of a given subcellular structure by fluorescence light microscopy (FLM) and electron microscopy. The use of this approach is becoming increasingly frequent in cell biology. In this study, we report on a new high data output CLEM method based on the use of cryosections. We successfully applied the method to analyze the structure of rough and smooth Russell bodies used as model systems. The major advantages of our method are (i) the possibility to correlate several hundreds of events at the same time, (ii) the possibility to perform three-dimensional (3D) correlation, (iii) the possibility to immunolabel both endogenous and recombinantly expressed proteins at the same time and (iv) the possibility to combine the high data analysis capability of FLM with the high precision–accuracy of transmission electron microscopy in a CLEM hybrid morphometry analysis. We have identified and optimized critical steps in sample preparation, defined routines for sample analysis and retracing of regions of interest, developed software for semi/fully automatic 3D reconstruction and defined preliminary conditions for an hybrid light/electron microscopy morphometry approach

    Tracking and Mapping in Medical Computer Vision: A Review

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    As computer vision algorithms are becoming more capable, their applications in clinical systems will become more pervasive. These applications include diagnostics such as colonoscopy and bronchoscopy, guiding biopsies and minimally invasive interventions and surgery, automating instrument motion and providing image guidance using pre-operative scans. Many of these applications depend on the specific visual nature of medical scenes and require designing and applying algorithms to perform in this environment. In this review, we provide an update to the field of camera-based tracking and scene mapping in surgery and diagnostics in medical computer vision. We begin with describing our review process, which results in a final list of 515 papers that we cover. We then give a high-level summary of the state of the art and provide relevant background for those who need tracking and mapping for their clinical applications. We then review datasets provided in the field and the clinical needs therein. Then, we delve in depth into the algorithmic side, and summarize recent developments, which should be especially useful for algorithm designers and to those looking to understand the capability of off-the-shelf methods. We focus on algorithms for deformable environments while also reviewing the essential building blocks in rigid tracking and mapping since there is a large amount of crossover in methods. Finally, we discuss the current state of the tracking and mapping methods along with needs for future algorithms, needs for quantification, and the viability of clinical applications in the field. We conclude that new methods need to be designed or combined to support clinical applications in deformable environments, and more focus needs to be put into collecting datasets for training and evaluation.Comment: 31 pages, 17 figure

    The Industrial Track of EuroVR 2018:Proceedings of the 15th Annual EuroVR Conference

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    The Industrial Track of EuroVR 2018:Proceedings of the 15th Annual EuroVR Conference

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    Infants at high risk of cerebral palsy:Neuromotor characteristics and the effect of the early intervention programme COPCA

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    Worldwide, over 140 million babies are born each year. Most of them are healthy and will develop typically, but some infants are at risk of neurodevelopmental disorders like cerebral palsy. The primary aim of this thesis was to enhance the identification of infants at risk of cerebral palsy (CP) and to improve prediction of future neurodevelopment. To this end, we first reviewed the literature on the predictive value of specific neurological signs in high-risk infants (chapter 2). Next, we explored possible relationships between slow pupillary light responses and type of brain lesion and developmental outcome (chapter 3). We analyzed knee jerk responses by means of surface electromyography (EMG) in both healthy newborns and high-risk infants (chapter 4), and we investigated whether the development of knee jerk responses was associated with a specific type of brain lesion or diagnosis of CP (chapter 5). Furthermore, we evaluated whether specific movement characteristics could enhance the predictive power of definitely abnormal general movements (GMs; chapter 6 and 7). Our secondary aim was to investigate the effect of the early intervention programme COPCA (COPing with and CAring for infants with special needs – a family centred programme) in infants identified as being at risk of CP. We presented the follow-up data of the VIP project (Dutch: Vroegtijdig Interventie Project, chapter 8) and the research design of the LEARN2MOVE 0-2 (L2M 0-2) years study (chapter 9)
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