Apparatus and methods for real-time image generation

1. An apparatus for real time image generation, the apparatus comprising:

at least an optical system;

a slide port configured to hold a slide;

an actuator mechanism mechanically connected to a mobile element;

a user interface comprising an input interface and an output interface;

at least a processor; and

a memory communicatively connected to the at least processor, the memory containing instructions configuring the at least processor to:

using the at least an optical system, capture a first image of the slide at a first position;

modify the first image;

using the output interface, display the first image to a user;

using the input interface, receive a parameter set from the user;

using the actuator mechanism, move the mobile element into a second position, wherein the second position is determined based on the parameter set;

using the at least an optical system, capture a second image of the slide at the second position;

modify the second image; and

using the output interface, display the second image to the user.

2. The apparatus of claim 1 , wherein moving the mobile element into the second position comprises:

positioning, using the actuator mechanism, the slide relative to the at least an optical system such that a region of interest defined by the parameter set is within a frame of at least an optical sensor of the at least an optical system; and

setting a zoom of the at least an optical system based on a level of zoom specified by the parameter set.

3. The apparatus of claim 1 , wherein moving the mobile element into a second position comprises setting a focus height of the at least an optical system based on a focus height specified by the parameter set.

4. The apparatus of claim 1 , wherein moving the mobile element into a second position comprises:

detecting a sample height at the region of interest; and

setting a focus height of the at least an optical system based on the sample height at the region of interest.

5. The apparatus of claim 1 , wherein the second image is captured using a higher level of zoom than that used to capture the first image.

6. The apparatus of claim 5 , wherein modifying the second image comprises:

replacing at least a region of the first image with the second image to create a hybrid second image; and

displaying the hybrid second image to the user.

7. The apparatus of claim 6 , wherein modifying the first image comprises:

receiving, using the user interface, an annotation instruction from the user; and

adding an annotation to the first image based on the annotation instruction.

8. The apparatus of claim 7 , wherein the memory contains instructions configuring the at least a processor to:

train an annotation machine learning model using a training dataset including image data associated with a feature depicted by the image;

input into the annotation machine learning model an image selected from the list consisting of the first image, the second image, and the hybrid image;

receive from the annotation machine learning model a datum identifying a feature depicted by the image selected from the list consisting of the first image, the second image, and the hybrid image; and

add an annotation to the first image, as a function of the image feature.

9. The apparatus of claim 1 , wherein modifying the first image comprises:

removing a first artifact from the first image, wherein removing the first artifact comprises:

inputting the first image into an artifact removal machine learning model; and

receiving, from the artifact removal machine learning model, a version of first image lacking the artifact.

10. The apparatus of claim 9 , wherein t modifying the second image comprises:

removing a second artifact from the second image, wherein removing the second artifact comprises:

inputting the second image into an artifact removal machine learning model; and

receiving from the artifact removal machine learning model a version of second image lacking the artifact.

11. A method of real time image generation, the method comprising:

using at least a processor and at least an optical system, capturing a first image of the slide at a first position;

using the at least a processor, modify the first image;

using the at least a processor and an output interface, displaying the first image to a user;

using the at least a processor and an input interface, receiving a parameter set from the user;

using the at least a processor and an actuator mechanism, moving the mobile element into a second position, wherein the second position is determined based on the parameter set;

using the at least a processor and the at least an optical system, capturing a second image of the slide at the second position;

using the at least a processor, modify the first image; and

using the at least a processor and the output interface, displaying the second image to the user.

12. The method of claim 11 , wherein moving the mobile element into the second position comprises:

positioning, using the actuator mechanism, the slide relative to the at least an optical system such that a region of interest defined by the parameter set is within a frame of at least an optical sensor of the at least an optical system; and

setting a zoom of the at least an optical system based on a level of zoom specified by the parameter set.

13. The method of claim 11 , wherein moving the mobile element into a second position comprises setting a focus height of the at least an optical system based on a focus height specified by the parameter set.

14. The method of claim 11 , wherein moving the mobile element into a second position comprises:

detecting a sample height at the region of interest; and

setting a focus height of the at least an optical system based on the sample height at the region of interest.

15. The method of claim 11 , wherein the second image is captured using a higher level of zoom than that used to capture the first image.

16. The method of claim 15 , wherein modifying the second image comprises:

replacing at least a region of the first image with the second image to create a hybrid second image; and

displaying the hybrid second image to the user.

17. The method of claim 16 , wherein modifying the first image comprises:

receiving, using the user interface, an annotation instruction from the user; and

adding an annotation to an image selected from to the first image, based on the annotation instruction.

18. The method of claim 16 , wherein modifying the first image comprises:

training an annotation machine learning model using a training dataset including image data associated with a feature depicted by the image;

inputting into the annotation machine learning model an image selected from the list consisting of the first image, the second image, and the hybrid second image;

receiving from the annotation machine learning model a datum identifying a feature depicted by the image selected from the list consisting of the first image, the second image, and the hybrid second image; and

adding an annotation to the first image, as a function of the image feature.

19. The method of claim 11 , wherein modifying the first image comprises:

removing a first artifact from the first image, wherein removing the first artifact comprises:

inputting the first image into an artifact removal machine learning model; and

receiving, from the artifact removal machine learning model, a version of first image lacking the artifact.

20. The method of claim 11 , wherein modifying the second image comprises:

removing a second artifact from the second image, wherein removing the second artifact comprises:

inputting the second image into an artifact removal machine learning model; and

receiving from the artifact removal machine learning model a version of second image lacking the artifact.