US-12625358-B2 - Method comprising determining a quantitative dispersion image of an object and digital in-line hologram microscope scanner

Abstract

A method comprising determining a quantitative dispersion image of an object based on a set of quantitative phase images, each quantitative phase image of the set of quantitative phase images having been obtained with a respective different illumination light wavelength.

Inventors

• Paul Springer
• Thimo EMMERICH
• Zoltan Facius
• Matthias SCHINZEL

Assignees

• Sony Group Corporation

Dates

Publication Date

20260512

Application Date

20210709

Priority Date

20200710

Claims (20)

1. 1 . A method comprising: determining a quantitative dispersion image of an object based on a set of quantitative phase images, each quantitative phase image of the set of quantitative phase images having been obtained with a respective different illumination light wavelength, wherein the set of quantitative phase images comprises three quantitative phase images, wherein each of the three phase images having been obtained with one of three different illumination light wavelengths which are ordered as, wherein λ short is the shortest wavelength of the three different wavelengths, λ middle is the middle wavelength of the three different wavelengths and Δ long is the longest wavelength of the three different wavelengths.
2. 2 . The method of claim 1 further comprising, calculating, for each different illumination light wavelength, the respective phase image based on respective one or more phase-shifted holograms of the object.
3. 3 . The method of claim 2 further comprising, determining a quantitative phase image of the object for each three different illumination light wavelengths by applying a Gerchberg-Saxton algorithm to the respective one or more phase-shifted holograms of the object for each three different illumination light wavelengths.
4. 4 . The method of claim 1 further comprising, acquiring, for each different illumination light wavelength, respectively one or more phase-shifted holograms of the object at an image sensor.
5. 5 . The method of claim 4 , wherein the respective one or more phase-shifted holograms of the object are acquired time sequentially for each of the different illumination light wavelengths and wherein the image sensor is a monochrome image sensor.
6. 6 . The method of claim 4 , wherein the acquiring of two or more phase-shifted holograms of the object comprises shifting the distance between the image sensor and the object to realize different phase shifts.
7. 7 . The method of claim 4 , wherein the acquiring of two or more phase-shifted holograms of the object comprises tuning a tunable phase-shifter which is placed between the object and the image sensor to realize different phase shifts.
8. 8 . The method of claim 4 , wherein the acquiring of two or more phase-shifted holograms of the object comprises inserting different swappable elements with different refractive indices between the image sensor and the object to realize different phase shifts or comprises inserting different optical elements with different thickness between the image sensor and the object to realize different phase shifts.
9. 9 . The method of claim 4 , wherein the acquiring of two or more phase-shifted holograms of the object comprises switching a polarizer placed on top of a birefringent optical element which are placed between the object and the image sensor to realize different phase shifts.
10. 10 . The method of claim 1 , wherein the determining the quantitative dispersion image of the object comprises calculating, for each of different illumination light wavelengths and for each pixel of the quantitative dispersion image, an optical path difference based on a phase delay value of a respective pixel of the respective quantitative phase image.
11. 11 . The method of claim 10 , wherein the determining a quantitative dispersion image of the object comprises calculating, for each of different illumination light wavelengths and for each pixel of the quantitative dispersion image, a refractive index based on a predetermined refractive index of a reference medium and the optical path difference of a respective pixel of the respective quantitative phase image.
12. 12 . The method of claim 11 , wherein the determining a quantitative dispersion image of the object comprises calculating, for each pixel of the quantitative dispersion image, a quantitative dispersion value based on the respective refractive indices of the different illumination light wavelengths.
13. 13 . The method of claim 1 , wherein the determining a quantitative dispersion image of the object comprises calculating, for each pixel of the quantitative dispersion image, a quantitative dispersion value, based on three refractive indices corresponding to the three different illumination light wavelengths QDV object = n middle , object - 1 n short , object - n long , object wherein the first refractive index n short of three refractive indices n short , n middle , n long corresponds to shortest illumination light wavelength λshort, the second refractive index n middle of three refractive indices n short , n middle , n long corresponds to middle illumination light wavelength λ middle and the third refractive index n long of three refractive indices n short , n middle , n long corresponds to the longest illumination light wavelength Δ long .
14. 14 . The method of claim 1 , wherein a virtual staining of the object is based on the quantitative dispersion image of the object.
15. 15 . The method of claim 1 , wherein the three different illumination light wavelengths are blue, green and red.
16. 16 . The method of claim 15 further comprising, calculating, for each different illumination light wavelength, a respective amplitude image based on respective one or more phase-shifted holograms of the object, and reconstructing an RGB image of the object based on the amplitude images.
17. 17 . The method of claim 16 , wherein the virtual staining of the object is based on the quantitative dispersion image of the object and/or the RGB image of the object and/or the qualitative phase image for each of the three different illumination light wavelengths.
18. 18 . The method of claim 1 , wherein the object is a tissue specimen.
19. 19 . An electronic device comprising circuitry configured to: determine a quantitative dispersion image of an object based on a set of quantitative phase images, each quantitative phase image of the set of quantitative phase images having been obtained with at least three different illumination light wavelengths which are ordered as, wherein λ short is the shortest wavelength of the three different wavelengths, λ middle is the middle wavelength of the three different wavelengths and λ long is the longest wavelength of the three different wavelengths.
20. 20 . A digital in-line hologram microscope scanner comprising: an image sensor configured to acquire, for each illumination light wavelength of a set of different illumination light wavelengths, respective two or more phase-shifted holograms of an object, wherein the distance between the object and the image sensor is fixed; and circuitry configured to; determine a set of quantitative phase images from the acquired phase-shifted holograms; and calculate, for each of different illumination light wavelengths and for each pixel of the quantitative dispersion image, an optical path difference based on a phase delay value of a respective pixel of the respective quantitative phase image.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS The present application is based on PCT filing PCT/EP2021/069187, filed Jul. 9, 2021, which claims priorities to EP 20185349.6, filed on Jul. 10, 2020, the entire contents of each are incorporated herein by reference. TECHNICAL FIELD The present disclosure generally pertains to the field of holographic microscopy, in particular to devices, methods and systems for time-sequential partially coherent illumination based holographic microscopy scanners. TECHNICAL BACKGROUND In the field of digital pathology imaging automatic analysis of tissue specimen is facilitated by applying image acquisition under brightfield condition using an RGB scanner. Sufficient imaging contrast is needed in order to make it possible to digitize a thin sliced tissue specimen by the use of a visible light RGB scanner. This is achieved by staining (labeling) the specimen with a histochemical dye, whereby sufficient imaging contrast is provided to make it possible to use the visible light RGB scanner. Thereby, the specimen is transformed from, a phase-altering object (only phase of transmitted light changes, not the amplitude) into an amplitude-altering object. Frequently used histochemical dyes are Hematoxylin and Eosin (HE), which create the desired imaging contrast and reveal tissue morphology on the cellular and the subcellular level. However, the staining process suffers from several disadvantages, which especially make automated image analysis difficult, for example image analysis based on machine learning. For example, the digitized tissue specimen can show a huge variability in the appearance of the histochemical dye caused by different lab protocols (e.g. leading to different application time of HE) or caused by different chemical formulation of reagents among different labs or caused by different specimen thickness. Another disadvantage can be that the staining process is time consuming, especially if additional staining is required. Still another disadvantage can be the staining process is expensive if non-common reagents are necessary. Still another disadvantage can be that the chemical effects deform structures of the specimen. Therefore, a technique known as virtual staining can be applied to an object which overcome some of the above-mentioned disadvantages. In virtual staining of an object, a digital representation that is equivalent to a chemically stained version of the object is created and thereby histochemical staining can be avoided. Therefore, it is desirable to improve the virtual staining technique. SUMMARY According to a first aspect the disclosure provides a method comprising determining a quantitative dispersion image of an object based on a set of quantitative phase images, each quantitative phase image of the set of quantitative phase images having been obtained with a respective different illumination light wavelength. According to a further aspect the disclosure provides an electronic device comprising circuitry configured to acquiring with at least three different illumination light wavelengths respectively one or more phase-shifted holograms of an object at an image sensor. According to a further aspect the disclosure provides a digital in-line hologram microscope scanner comprising, an image sensor configured to acquire, for each illumination light wavelength of a set of different illumination light wavelengths, respective two or more phase-shifted holograms of an object. Further aspects are set forth in the dependent claims, the following description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS Embodiments are explained by way of example with respect to the accompanying drawings, in which: FIG. 1 shows a digital-in-line holographic microscopy (DIHM) scanner with a multi-height phase shift concept; FIG. 2 shows a digital in-line holographic microscopy (DIHM) scanner with a tuneable phase-shifter using a liquid crystal phase shift concept; FIG. 3 shows a digital in-line holographic microscopy (DIHM) scanner with different swappable optical elements to realize phase shift concept; FIG. 4 shows a digital in-line holographic microscopy (DIHM) scanner with a switchable polarizer and a birefringent optical element to realize phase shift concept; FIG. 5 shows a flow chart of the process of capturing different holograms; FIG. 6 shows process steps for a virtual staining process operated on an unstained input object (tissue specimen); FIG. 7 shows a flow chart of the Gerchberg-Saxton algorithm; FIG. 8 shows a flow chart of the calculation of the quantitative dispersion image (QDI); FIG. 9 shows a flow chart of generating a trained classifier for virtual staining; FIG. 10a shows a flow chart of a process of virtual staining of an object; FIG. 10b shows a table of QDI pixel values and their corresponding classification; FIG. 11 shows different virtual staining operations that can be applied to a stained tissue specimen, input to the DIHM scanner; FIG. 12 shows differe