Method for generating and analyzing an overview contrast image

Patent metadata

Field	Value
Publication number	US-11307398-B2
Application number	US-201816618773-A
Country	US
Kind code	B2
Filing date	May 15, 2018
Priority date	May 30, 2017
Publication date	Apr 19, 2022
Grant date	Apr 19, 2022

Abstract

A method for generating and analyzing an overview contrast image of a specimen carrier and/or of specimens situated on a specimen carrier. A specimen carrier arranged at least partially in the focus of a detection optical unit is illuminated in transmitted light using a two-dimensional, array-like illumination pattern. At least two overview raw images are detected using different illuminations of the specimen carrier, and, according to information to be extracted from the overview contrast image, a combination algorithm is selected by means of which the at least two overview raw images are combined to form the overview contrast image. According to information to be extracted from the overview contrast image, an image evaluation algorithm is selected by means of which the information is extracted.

First claim

The invention claimed is:

1. A method for producing and analyzing an overview contrast image of a sample carrier or of samples arranged on said sample carrier or of both the sample carrier and the samples arranged on said sample carrier, comprising:
illuminating the sample carrier, which is arranged at least partially in a focus of a detection optical unit, in transmitted light with a two-dimensional, array-type illumination pattern,
detecting at least two overview raw images with different illuminations of the sample carrier,
choosing a calculation algorithm that is used to calculate the overview contrast image with an increased contrast or an improved signal-to-noise ratio from the at least two overview raw images in dependence on information that is to be extracted from the overview contrast image, and
choosing an image evaluation algorithm that is used to extract the information from the overview contrast image in dependence on information that is to be extracted from the overview contrast image.

2. The method as claimed in claim 1 , further comprising producing illumination patterns using an array having same-sized illumination elements, wherein the individual illumination elements are in each case distinguishable from one another in the at least two overview raw images.

3. The method as claimed in claim 2 , wherein the illumination elements used are light emitting diodes (LED), organic light emitting diodes OLED), optical fibers, elements of an illuminated digital micromirror device (DMD) or of a spatial light modulator (SLM).

4. The method as claimed in claim 1 , further comprising-producing the different illuminations by laterally moving the sample carrier relative to the illumination pattern between two recordings or by using different exposure times for the detection.

5. The method as claimed in claim 4 , further comprising combining the individual contrast images that each show different regions of the sample carrier or the sample or of both the sample carrier and the sample to form the overview contrast image.

6. The method as claimed in claim 2 , further comprising producing the different illuminations using different illumination patterns, which are chosen in dependence on the information that is to be extracted.

7. The method as claimed in claim 6 , wherein producing different illumination patterns includes driving the illumination elements individually or in groups, and switching to produce different illumination patterns, wherein a first portion of the illumination elements is switched to emit light and at least a second portion of the illumination elements is switched to emit no light or to emit light of a different color or light of a different polarization.

8. The method as claimed in claim 7 , wherein the different illumination patterns are produced by:
stochastically choosing the first portion of the illumination elements for each illumination pattern, or
stochastically choosing the first portion of the illumination elements having a chessboard-type or a different regular distribution, the different regular distribution being a cross-shaped distribution or a half pupil distribution in the array.

9. The method as claimed in claim 8 , comprising stochastically choosing the first portion of the illumination elements having a chessboard-type or a different regular distribution, in which the second portion of the illumination elements does not emit light, and at least two overview raw images are recorded with mutually complementary illumination patterns.

10. The method as claimed in claim 8 , comprising stochastically choosing the first portion of the illumination elements having a chessboard-type or a different regular distribution, in which all portions of the illumination elements emit light of colors or polarizations that differ from one another in pairs, further comprising recording simultaneously in an image a number of overview raw images, which corresponds to the number of portions, and subsequently separating the image by color channels or polarization.

11. The method as claimed in claim 6 , wherein LEDs or OLEDs are used as the illumination elements, and the method further comprises producing stochastic illumination patterns by using pulse-width-modulated illumination elements having a pulse width that is selected to be longer than an integration time of a detector unit for recording the overview raw images.

12. The method as claimed in claim 6 , wherein the illumination pattern is produced only in at least one section of the array of illumination elements, and the different illuminations are produced by scanning movement of the at least one section on the array, wherein the illumination elements outside the at least one section are switched to emit no light.

13. The method as claimed in claim 6 , wherein the illumination elements are in the form of LEDs, wherein an LED is formed from three individual mutually adjacent sub-LEDs that each emit light in different primary colors red, green and blue, and different illuminations are set by the illumination from different angles in the primary colors.

14. The method as claimed in claim 1 , further comprising choosing a calculation algorithm for producing an overview contrast image in a dark-field or bright-field mode in dependence on selection of an illumination method.

15. The method as claimed in claim 14 , wherein:
the calculation algorithm is based on pixel-wise projection, including on a ranking projection or on a projection of statistical moments, wherein, for producing the overview contrast image from a stack of at least two overview raw images, the overview raw images are compared pixel by pixel, and the intensity value of one of the pixels for the corresponding position in the overview contrast image is chosen in accordance with a projection condition, or
the calculation algorithm is based on morphological operations with subsequent pixel-wise projection, including on a top-hat or black-hat transform with subsequent pixel-wise maximum projection, or
a calculation algorithm based on segmentation is selected, in which initially a determination is made for each pixel of an overview raw image as to whether it was irradiated directly with light by an illumination element, and said pixels are not taken into account for producing an overview contrast image in dark-field contrast mode.

16. The method as claimed in claim 2 , further comprising performing a calibration for correcting geometric distortions using a recording and evaluation of a calibration pattern before the recording of overview raw images, wherein the calibration pattern is produced with the illumination elements of the array.

17. The method as claimed in claim 1 , removing disturbing background signals from the overview contrast image before the evaluation.

18. The method as claimed in claim 1 , further comprising:
introducing a diffusion screen between the array-type illumination pattern and the sample carrier, or switching a switchable diffusion screen to a diffusing mode,
wherein the overview contrast image is produced in a bright-field mode.

19. The method as claimed in claim 1 , the image evaluation algorithm chosen is a machine learning algorithm, the machine learning algorithm being a deep learning algorithm, which is trained on a basis of overview contrast images with known information.

20. The method as claimed in claim 19 , further comprising:
using a deep learning algorithm based on a convolutional neural network to identify a type of the sample carrier,
performing a

Assignees

• Zeiss Carl Microscopy Gmbh

Inventors

• Haase Daniel
• Ohrt Thomas
• Sticker Markus

Classifications

• G02B21/367 Primary

  providing an output produced by processing a plurality of individual source images, e.g. image tiling, montage, composite images, depth sectioning, image comparison · CPC title

• G02B21/125 Primary

  affording both dark- and bright-field illumination · CPC title

• G02B21/086

  for transillumination only · CPC title