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Home: Anjaneya AutomationFrom Idea to Intelligent Machines
Medical imagingWhole-slide imagingAI inside

A lab microscope turned into an AI slide scanner

We added X, Y and Z axes to a lab microscope so it captures a whole slide tile by tile and stitches it into one image. Our AI software then flags suspected cancer cells, using the settings the doctor or lab technician chooses.

The upgraded microscope with its motorized stage, beside a screen showing slide tiles stitched into one image and regions marked by the AI
How it works: X, Y and Z axes move the slide, the tiles are stitched into a whole-slide image, and the AI marks suspicious cells
The software: scan control, scan progress, analysis settings, a flagged region with its confidence, and a heatmap of the slide

From one small view to the whole slide

A microscope sees a small circle of the slide at a time. Our upgrade moves the slide under the lens, captures all of it, and gives the doctor one image with the findings marked.

axes added: X, Y and Z
3
image of the entire slide
1
  1. 01

    The mechanism

    Motion added to the microscope, so the slide moves and focuses under control.

    • X and Y axes for the slide
    • Z axis for focus and zoom
    • Precise, repeatable steps
    • Built onto the existing microscope
  2. 02

    Whole-slide imaging

    The slide is captured tile by tile and stitched into one image you can pan and zoom.

    • Thousands of tiles per slide
    • Auto focus
    • Stitched into one image
    • Overview with pan and zoom
  3. 03

    AI analysis

    The software marks suspected cancer cells, working to the doctor's or technician's settings.

    • Suspected cancer cells and regions
    • A confidence and heatmap for each slide
    • Sensitivity, threshold and cell types set by your lab
    • Measurements and reports

The challenge

A microscope shows only a small part of a slide at a time. Checking a whole tissue sample means moving the slide by hand, refocusing again and again and looking through thousands of fields one by one: slow, tiring work in which a small group of abnormal cells is easy to miss.

What we built

We added motion to the microscope: X and Y axes that move the slide in precise steps, and a Z axis for focus and zoom. The system captures the slide as thousands of small tiles and stitches them into one high-resolution image of the entire slide. Our software then analyses the cells with AI and highlights suspected cancer cells and regions, according to the sensitivity, threshold and cell types the doctor or lab technician sets. Every finding is shown to them for review; the final decision stays with the doctor.

Engineering highlights

  • X and Y axes added to a standard lab microscope, moving the slide in precise, repeatable steps
  • A Z axis for focus and zoom, with auto focus before the scan
  • Thousands of tiles captured per slide and stitched into one whole-slide image
  • AI that outlines suspected cancer cells and regions, with a confidence for each and a heatmap of the slide
  • Sensitivity, probability threshold and cell types set by the doctor or lab technician
  • Each finding measured (area and perimeter) and added to the report in one click

Scan, stitch, analyse, review

  1. 01

    Load and focus

    Place the slide and set the home position. The Z axis finds the focus.

    • Home position
    • Auto focus
  2. 02

    Scan tile by tile

    The X and Y axes move the slide in small steps while the camera captures each field.

    • Thousands of tiles
  3. 03

    Stitch

    The tiles are joined into one high-resolution image of the entire slide.

    • Whole-slide image
  4. 04

    Analyse and review

    The AI marks suspected cancer cells using your settings. The doctor reviews each finding and adds it to the report.

    • Findings
    • Heatmap
    • Report

AI that works to your lab's settings

The software doesn't decide on its own. Doctors and lab technicians choose what it looks for and how sure it must be, and every finding comes back to them for review.

  • Cell detection

    Finds and outlines suspected cancer cells and regions across the whole slide.

  • Your sensitivity and threshold

    Set how sensitive the detection is, and the probability a finding must reach before it is shown.

  • Cell types to look for

    Choose which cell types to flag, such as carcinoma, lymphocytes, stroma or necrosis.

  • A confidence for every finding

    Each flagged region shows its class and how confident the AI is, so it can be checked quickly.

  • Heatmap of the slide

    See at a glance where on the slide the suspicious areas are.

  • Measured and reported

    The area and perimeter of each region, added to the report with one click.

From Idea to Intelligent Machines

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