Systems and methods for determining cell number count in automated stereology z-stack images

A method comprising:

• obtaining a sequence of images having varying focus and including a plurality of cellular structures;
• applying the sequence of images to a trained deep-learning model;
• determining, for each respective cellular structure, respective context information from a plurality of the images;
• identifying, for each respective cellular structure, an associated image of the sequence for segmentation of the cellular structure based on the respective context information;
• and
• generating a segmented output identifying each cellular structure in its respective associated image.

A computer-readable medium storing executable instructions to:

• obtain a sequence of images having varying focus and including a plurality of cellular structures;
• apply the sequence of images to a trained deep-learning model;
• determine, for each respective cellular structure, respective context information from a plurality of the images;
• identify, for each respective cellular structure, an associated image of the sequence for segmentation of the cellular structure based on the respective context information;
• and
• generate a segmented output identifying each cellular structure in its respective associated image.

A computing system comprising:

• a processor;
• and
• a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising:
• obtaining a sequence of images having varying focus and including a plurality of cellular structures;
• applying the sequence of images to a trained deep-learning model;
• determining, for each respective cellular structure, respective context information from a plurality of the images;
• identifying, for each respective cellular structure, an associated image of the sequence for segmentation of the cellular structure based on the respective context information;
• and
• generating a segmented output identifying each cellular structure in its respective associated image.