Patent ID: 11948295
Assignee: RAMOT AT TEL-AVIV UNIVERSITY LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system for visualizing an unstained sperm cell, the system comprising:
a data input utility configured and operable for receiving measured data comprising at least one quantitative phase microscopy image of the unstained sperm cell;
a data processing utility comprising:
an image analyzer module configured and operable to utilize characteristic refractive index information of one or more organelles of the sperm cell, to process said at least one quantitative phase microscopy image and generate at least one corresponding gradient image that includes edge enhancement of said one or more organelles; and
a virtual staining module configured and operable to apply one or more predetermined virtual staining functions to said at least one quantitative phase microscopy image and at least one corresponding gradient image, thereby virtually stain at least one of said one or more organelles of the sperm cell and generate virtually stained image data of the sperm cell; and
an output utility configured and operable to utilize said virtually stained image data of the sperm cell and generate one or more stained images of the unstained sperm cell, each emulating an image of the sperm cell should the sperm cell has been actually stained with one or more actual stains;
wherein said data processing utility comprises a virtual staining function generator module being configured and operable to create at least one of said one or more virtual staining functions by performing the following:
receiving first measured data of a plurality of quantitative phase images of a respective plurality of unstained sperm cells, and second measured data of a respective plurality of bright field microscopy images corresponding to one of the following: the plurality of the sperm cells after being stained with a specific stain; or the plurality of sperm cells stained with a specific stain, and
processing the first and second measured data utilizing machine deep learning to generate the at least one virtual staining function pertaining to the specific stain.