A Model-based approach for microvasculature structure distortion correction in two-photon fluorescence microscopy images

This paper investigates a postprocessing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modelling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to subvolumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional (3D) spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images.

Motion compensation for in vivo subcellular optical microscopy

In this review, we focus on the impact of tissue motion on attempting to conduct subcellular resolution optical microscopy, in vivo. Our position is that tissue motion is one of the major barriers in conducting these studies along with light induced damage, optical probe loading as well as absorbing and scattering effects on the excitation point spread function and collection of emitted light. Recent developments in the speed of image acquisition have reached the limit, in most cases, where the signal from a subcellular voxel limits the speed and not the scanning rate of the microscope. Different schemes for compensating for tissue displacements due to rigid body and deformation are presented from tissue restriction, gating, adaptive gating and active tissue tracking. We argue that methods that minimally impact the natural physiological motion of the tissue are desirable because the major reason to perform in vivo studies is to evaluate normal physiological functions. Towards this goal, active tracking using the optical imaging data itself to monitor tissue displacement and either prospectively or retrospectively correct for the motion without affecting physiological processes is desirable. Critical for this development was the implementation of near real time image processing in conjunction with the control of the microscope imaging parameters. Clearly, the continuing development of methods of motion compensation as well as significant technological solutions to the other barriers to tissue subcellular optical imaging in vivo, including optical aberrations and overall signal-to-noise ratio, will make major contributions to the understanding of cell biology within the body.

Use of independent component analysis to improve signal-to-noise ratio in multi-probe fluorescence microscopy

In conventional multi-probe fluorescence microscopy, narrow bandwidth filters on detectors are used to avoid bleed-through artefacts between probes. The limited bandwidth reduces the signal-to-noise ratio of the detection, often severely compromising one or more channels. Herein, we describe a process of using independent component analysis to discriminate the position of different probes using only a dichroic mirror to differentiate the signals directed to the detectors. Independent component analysis was particularly effective in samples where the spatial overlap between the probes is minimal, a very common case in cellular microscopy. This imaging scheme collects nearly all of the emitted light, significantly improving the image signal-to-noise ratio. In this study, we focused on the detection of two fluorescence probes used in vivo, NAD(P)H and ANEPPS. The optimal dichroic mirror cutoff frequency was determined with simulations using the probes spectral emissions. A quality factor, defined as the cross-channel contrast-to-noise ratio, was optimized to maximize signals while maintaining spatial discrimination between the probes after independent component analysis post-processing. Simulations indicate that a ∼3 fold increase in signal-to-noise ratio using the independent component analysis approach can be achieved over the conventional narrow-band filtering approach without loss of spatial discrimination. We confirmed this predicted performance from experimental imaging of NAD(P)H and ANEPPS in mouse skeletal muscle, in vivo. For many multi-probe studies, the increased sensitivity of this 'full bandwidth' approach will lead to improved image quality and/or reduced excitation power requirements.