Exploring the optimal fluorescein dose in probe-based confocal laser endomicroscopy for colonic imaging.

BACKGROUND: Probe-based confocal laser endomicroscopy (pCLE) is an emerging method for in-vivo imaging of the gastrointestinal tract and requires a contrast agent. Fluorescein is the most commonly used agent. The optimal dose of fluorescein for pCLE in colon is unknown. OBJECTIVE: Exploration of optimal dose of fluorescein for pCLE in colon. DESIGN: Comparative, prospective pilot trail. SETTING: Tertiary-care center. PATIENTS: 18 participants underwent colonoscopy without complications. INTERVENTIONS: pCLE videos were recorded in normal cecum, using 10% fluorescein intravenously. MAIN OUTCOME MEASUREMENTS: For subjective analysis, pCLE videos were scored for quality, by 2 observers, independently and blinded to fluorescein dose. For objective analysis, signal-to-noise ratios (SNR) were calculated for each video by an expert. RESULTS: 6 fluorescein doses were used, including 0.5 mL, 1 mL, 2.5 mL, 5 mL, 7.5 mL and 10 mL and each dose was used in three patients. For each dose, median image quality score was 2.5, 2.0, 3.25, 4.0, 4.0 and 3.5 by first observer and 2.0, 3.0, 4.0, 5.0, 4.0 and 4.0 by second observer, respectively. The subjective quality scores increased from 0.5 mL to 5.0 mL, with no evidence of further improved quality at 7.5 mL and 10 mL doses. SNR were not significantly different between doses but trended higher for higher doses. LIMITATIONS: Small sample size. The results can not be applied to other parts of gastrointestinal tract i.e. duodenum, esophagus with different blood supply. CONCLUSION: This preliminary study suggests that the optimal dose of fluorescein for high quality pCLE imaging in colon is approximately 5.0 mL.

Diffeomorphic demons: efficient non-parametric image registration.

We propose an efficient non-parametric diffeomorphic image registration algorithm based on Thirion's demons algorithm. In the first part of this paper, we show that Thirion's demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. We provide strong theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage for the symmetric forces variant of the demons algorithm. We show on controlled experiments that this advantage is confirmed in practice and yields a faster convergence. In the second part of this paper, we adapt the optimization procedure underlying the demons algorithm to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of displacement fields by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the gold standard, available in controlled experiments, in terms of Jacobians.

Symmetric log-domain diffeomorphic Registration: a demons-based approach.

Modern morphometric studies use non-linear image registration to compare anatomies and perform group analysis. Recently, log-Euclidean approaches have contributed to promote the use of such computational anatomy tools by permitting simple computations of statistics on a rather large class of invertible spatial transformations. In this work, we propose a non-linear registration algorithm perfectly fit for log-Euclidean statistics on diffeomorphisms. Our algorithm works completely in the log-domain, i.e. it uses a stationary velocity field. This implies that we guarantee the invertibility of the deformation and have access to the true inverse transformation. This also means that our output can be directly used for log-Euclidean statistics without relying on the heavy computation of the log of the spatial transformation. As it is often desirable, our algorithm is symmetric with respect to the order of the input images. Furthermore, we use an alternate optimization approach related to Thirion's demons algorithm to provide a fast non-linear registration algorithm. First results show that our algorithm outperforms both the demons algorithm and the recently proposed diffeomorphic demons algorithm in terms of accuracy of the transformation while remaining computationally efficient.

Non-parametric diffeomorphic image registration with the demons algorithm.

We propose a non-parametric diffeomorphic image registration algorithm based on Thirion's demons algorithm. The demons algorithm can be seen as an optimization procedure on the entire space of displacement fields. The main idea of our algorithm is to adapt this procedure to a space of diffeomorphic transformations. In contrast to many diffeomorphic registration algorithms, our solution is computationally efficient since in practice it only replaces an addition of free form deformations by a few compositions. Our experiments show that in addition to being diffeomorphic, our algorithm provides results that are similar to the ones from the demons algorithm but with transformations that are much smoother and closer to the true ones in terms of Jacobians.

Insight into efficient image registration techniques and the demons algorithm.

As image registration becomes more and more central to many biomedical imaging applications, the efficiency of the algorithms becomes a key issue. Image registration is classically performed by optimizing a similarity criterion over a given spatial transformation space. Even if this problem is considered as almost solved for linear registration, we show in this paper that some tools that have recently been developed in the field of vision-based robot control can outperform classical solutions. The adequacy of these tools for linear image registration leads us to revisit non-linear registration and allows us to provide interesting theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage to the symmetric forces variant of the demons algorithm. We show that, on controlled experiments, this advantage is confirmed, and yields a faster convergence.

Robust mosaicing with correction of motion distortions and tissue deformations for in vivo fibered microscopy.

Real-time in vivo and in situ imaging at the cellular level can be achieved with fibered confocal microscopy. As interesting as dynamic sequences may be, there is a need for the biologist or physician to get an efficient and complete representation of the entire imaged region. For this demand, the potential of this imaging modality is enhanced by using video mosaicing techniques. Classical mosaicing algorithms do not take into account the characteristics of fibered confocal microscopy, namely motion distortions, irregularly sampled frames and non-rigid deformations of the imaged tissue. Our approach is based on a hierarchical framework that is able to recover a globally consistent alignment of the input frames, to compensate for the motion distortions and to capture the non-rigid deformations. The proposed global alignment scheme is seen as an estimation problem on a Lie group. We model the relationship between the motion and the motion distortions to correct for these distortions. An efficient scattered data approximation scheme is proposed both for the construction of the mosaic and to adapt the demons registration algorithm to our irregularly sampled inputs. Controlled experiments have been conducted to evaluate the performance of our algorithm. Results on several sequences acquired in vivo on both human and mouse tissue also demonstrate the relevance of our approach.

Mosaicing of confocal microscopic in vivo soft tissue video sequences.

Fibered confocal microscopy allows in vivo and in situ imaging with cellular resolution. The potentiality of this imaging modality is extended in this work by using video mosaicing techniques. Two novelties are introduced. A robust estimator based on statistics for Riemannian manifolds is developed to find a globally consistent mapping of the input frames to a common coordinate system. A mosaicing framework using an efficient scattered data fitting method is proposed in order to take into account the non-rigid deformations and the irregular sampling implied by in vivo fibered confocal microscopy. Results on 50 images of a live mouse colon demonstrate the effectiveness of the proposed method.

Fibered confocal fluorescence microscopy (Cell-viZio) facilitates extended imaging in the field of microcirculation. A comparison with intravital microscopy.

This study investigated the capability of fibered confocal fluorescence microscopy (FCFM) to provide in vivo microvascular observations. FCFM is specifically designed for in vivo in situ observation thanks to a probe composed of a fiber bundle and micro-optics having a diameter as small as 650 microm. In the first part of the study, we compared the main characteristics of FCFM with those of intravital fluorescence microscopy (IFM). A mouse cremaster preparation was used as a common basis to allow for imaging with both modalities. We discussed the feasibility of obtaining quantitative measurements usually provided by IFM in the context of FCFM: morphometry, capillary permeability, functional capillary density, vasoconstriction and dilation effects. In addition, the possibility to visualize fluorescent red blood cells or leukocytes was also evaluated. Phototoxicity issues and limitations of FCFM were also discussed. We showed that FCFM allows observations and measurements usually provided by IFM and that the real-time capability of the system, as well as the flexibility and small diameter of the optical probe enable micro-invasiveness and can extend imaging capabilities for in vivo in situ observations when compared to IFM.