Content aware multi-focus image fusion for high-magnification blood film microscopy

Automated digital high-magnification optical microscopy is key to accelerating biology research and improving pathology clinical pathways. High magnification objectives with large numerical apertures are usually preferred to resolve the fine structural details of biological samples, but they have a very limited depth-of-field. Depending on the thickness of the sample, analysis of specimens typically requires the acquisition of multiple images at different focal planes for each field-of-view, followed by the fusion of these planes into an extended depth-of-field image. This translates into low scanning speeds, increased storage space, and processing time not suitable for high-throughput clinical use. We introduce a novel content-aware multi-focus image fusion approach based on deep learning which extends the depth-of-field of high magnification objectives effectively. We demonstrate the method with three examples, showing that highly accurate, detailed, extended depth of field images can be obtained at a lower axial sampling rate, using 2-fold fewer focal planes than normally required

Detection of acute promyelocytic leukemia in peripheral blood and bone marrow with annotation-free deep learning

While optical microscopy inspection of blood films and bone marrow aspirates by a hematologist is a crucial step in establishing diagnosis of acute leukemia, especially in low-resource settings where other diagnostic modalities are not available, the task remains time-consuming and prone to human inconsistencies. This has an impact especially in cases of Acute Promyelocytic Leukemia (APL) that require urgent treatment. Integration of automated computational hematopathology into clinical workflows can improve the throughput of these services and reduce cognitive human error. However, a major bottleneck in deploying such systems is a lack of sufficient cell morphological object-labels annotations to train deep learning models. We overcome this by leveraging patient diagnostic labels to train weakly-supervised models that detect different types of acute leukemia. We introduce a deep learning approach, Multiple Instance Learning for Leukocyte Identification (MILLIE), able to perform automated reliable analysis of blood films with minimal supervision. Without being trained to classify individual cells, MILLIE differentiates between acute lymphoblastic and myeloblastic leukemia in blood films. More importantly, MILLIE detects APL in blood films (AUC 0.94 ± 0.04) and in bone marrow aspirates (AUC 0.99 ± 0.01). MILLIE is a viable solution to augment the throughput of clinical pathways that require assessment of blood film microscopy

Spatially‐Resolved Spectroscopic Characterization of Reflective and Transparent Materials at a Micro‐Meter Scale Using Coherence Scanning Interferometry

International audienceThe development of new technologies and innovative products today is often accompanied by the emergence of new micro and nanomaterials. Due to their wider use in many applications, performing accurate characterization of these materials is becoming essential. The high performance of coherence scanning interferometry for materials characterization in terms of topographic, roughness and thickness measurements as well as for tomographic analysis of transparent layers has already been well demonstrated. However, demands regarding the spectral characterization of these materials requires new operation modes using the combination of spectral measurements with high resolution imaging. In this work we present a technique for local spectral measurements by careful processing of the entire interferometric signal over the scanned depth at each pixel in the image, so providing spatially resolved measurements in both the lateral and axial directions. Being a far‐field technique, and because the sample is illuminated with a white light source, spectral information is obtained over large areas (150 × 150 μm2) at the same time and for all the wavelengths. Spectroscopic mapping of a sample consisting of four different materials (Si, Al, Ag, Ti) and depth‐resolved measurements performed through a thin layer of PDMS are reported. Spectral measurements are made over an area of about 1–2 μm2, with an axial resolution of 1 μm, these features being dependent on the optical parameters of the system

Application of coherence scanning interferometry for local spectral characterization of transparent layers

International audienceIn the domain of optical metrology, white light interference microscopy is mainly known for performing micro and nano surface profilometry. This is achieved by identifying the envelope peak of the fringe signal. However, the polychromatic signal is rich in information and spectral characterization may be performed through the Fourier analysis of the signal, which gives local spectroscopic information about the sample surface. The use of CSI for studying transparent layers has also been well-developed since the analysis of the reflected light provides both structural and spectral information on the layer. Through the spectral analysis of the reflected light, it has been shown that the morphological properties of a thin film structure, namely the thickness and the refractive index, can be precisely measured. In this case, either the amplitude or the phase of the thin film total reflectance spectrum are used to recover the thickness. The technique is based on the best fit between the experimentally measured spectrum with that of the theoretical model using a non-linear least-squares algorithm. Usually, this spectral method is used to investigate thin films having a thickness that does not exceed a few hundred nanometers. In this work, we apply a similar technique, based on the magnitude of the total reflectance spectrum, to study thicker transparent layers. In this case, we show that precautions regarding the effective numerical aperture of the system need to be considered to obtain consistent values of both the refractive index and the thickness. In addition, we demonstrate the possibility of extracting the depth-resolved reflectance spectra of a buried interface independently from the spectral response of the surface. The consistency of these different spectra is demonstrated by comparing the results with those obtained using a program based on electromagnetic matrix methods for stratified media. The lateral spatial resolution of the measurements attained is a spot size of around 0.84 μm for spectrally characterizing small structures

Coherence scanning interferometry allows accurate characterization of micrometric spherical particles contained in complex media

International audienceCharacterizing very small particles, from a few dozen micrometers to the nanometric scale, is a very challenging application in a wide range of domains. In this work, we demonstrate, through the recovery of silica and polystyrene bead properties (i.e. their size and refractive index) that Coherence Scanning Interferometry (CSI), in addition of being contactless, non-destructive, label-free and very well spatially resolved, is a very interesting and promising tool for such complex characterization. The CSI system is used as an imaging Fourier transform spectrometer meaning that the characterizations are achieved by analyzing the interference signal in the spectral domain. Some simulations of the proposed technique are presented and show that the accuracy of such characterization, in particular the measurement of the refractive index, are closely related to the signal to noise ratio. This observation is thereafter confirmed by the experimental results of beads buried within the depth of a transparent sample. Finally, the method is theoretically tested in the case of a scattering medium in which the quality of the signal is highly degraded. In this context, a geometrical approach enabling the simulation of an interference signal from a scattering layer is first proposed and then validated by means of comparison with experimental data

Local inspection of refractive index and thickness of thick transparent layers using spectral reflectance measurements in low coherence scanning interferometry

International audienceFor a long time, obtaining the optical and morphological properties of a transparent sample with high accuracy without degrading the layer has been challenging. To achieve these expectations, contactless techniques are used and have not only been proven well-suitable but have also brought optical methods to the forefront. Over recent years white light scanning interferometry has been increasingly used for studying and characterizing transparent materials with thicknesses ranging from a few hundred nanometers to several micrometers. Then, multiple techniques have been developed to retrieve the transparent layer properties from interferometric data. The more recent techniques, based on the use of an error function which defines the best fit between the experimental and theoretical data, allow the determination of the thickness of very thin films (<1 μm). We show here that a method based on this principle can be applied to thicker layers (>1 μm) for simultaneously measuring their optical and morphological properties, provided that a crucial step is carefully considered during the data acquisition process. This enables the simultaneous measurements of both the thickness and the refractive index (dispersion) without any prior assumptions about one of the two parameters. We demonstrate the proposed method by accurate measurements on a few micrometers thick PMMA layer as well as on a SnO2 layer, which is a much more dispersive sample

Local reflectance spectra measurements of surfaces using coherence scanning interferometry

International audienceInterference microscopy is a widely used technique in optical metrology for the characterization of materials and in particular for measuring the micro and nanotopography of surfaces. Depending on the processing applied to the interference signal, either topographic analysis of the sample can be carried out by identifying the envelope peak of the fringe signal, which leads to 3D surface imaging, or spectral analysis may be performed which gives spectroscopic measurements. By applying a Fourier transform to the interference fringes, information about the source spectrum, the spectral response of the optical system, and the reflectance spectrum of the surface at the origin of the interferogram can be obtained. By using a sample of known reflectivity for calibration, it is possible to extract the spectral signature of the entire system and therefore to deduce that of the surface of interest. In this paper, we first explain theoretically how to retrieve the reflectance information of a surface from the interferometric signal. Then, we present some results obtained by this means with a white light scanning Linnik interferometer on different kinds of samples (silicon, tin oxide (SnO2), indium tin oxide (ITO)). The initial results were slightly different from those obtained with a conventional optical spectrometer until averaged temporally and were improved even further when averaged spatially. We show that the reflectance of the surface can be calculated over the given wavelength range of the effective spectrum, which is defined as the source spectrum multiplied by the spectral response of the camera and the spectral transmissivity of the optical system. We thus demonstrate that local spectroscopic measurements can be carried out with an interference microscope and that they match well with those measured with an optical spectrometer model Lambda19 UV-VIS-NIR from Perkin Elmer. A simulation study is also presented in order to validate the method and to help identify the potential sources of errors in the spectroscopic analysis