LeafYX · Automatic karyotyping

A classifier that learns from your laboratory’s karyotypes.

Automatic karyotyping uses a classifier chosen in the options. For each banding type the laboratory can use its own model, built on the workstation from the karyotypes it has verified.

Illustrative animation: not a screenshot of the program.

01 From list to model

Four steps, all on the workstation.

The laboratory verifies the karyotypes, gathers them in a list and generates the model that automatic karyotyping will work with.

  1. 01Verified karyotype

    From Processing, add it to the right list with one click.

  2. 02List

    Found from the case name and the banding type.

  3. 03Dataset

    Created from the karyotypes in the list.

  4. 04Model

    Generated, with the accuracy measured.

Operator control Automatic karyotyping is a suggestion, not a decision.

The result can always be corrected: each chromosome can be moved, swapped, rotated and flipped by hand, and reclassified. Training improves the suggestion; verification stays with the operator.

02 Training lists

One click from Processing, into the right list.

Once a karyotype has been checked, add it to the training list with one click. The program finds the list from the case name and the banding type.

  • One list and one model for each banding type.
  • List found from the case name and the banding type.
  • Creation and opening of lists recorded in the audit log.
  • Q-banding
  • G-banding
  • R-banding
FIG. 01Verified karyotype of a sample case and, below, the panel for adding it to the training list.

03 Comparison and training

One window to browse, create the dataset and generate the model.

The comparison and training window brings together the lists and the gallery. You check the material, create the dataset and generate the model.

  • Banding types3 · Q, G and R, one model each
  • Classes24 · human karyotype, including X and Y
  • List1 click to add a verified karyotype
  • GenerationA few minutes, even with hundreds of karyotypes *

* Indication from internal tests, not a guaranteed performance: the time depends on the computer and on the size of the list.

  • Browse the karyotypes in the lists and the gallery, to check what goes into the training.
  • Create the dataset from the karyotypes in the list.
  • Generate the model and show the measured accuracy.
  • During generation, a progress bar with elapsed time and estimated time.
  • The time estimate refines itself with each generation.
Sheet Classifier
Selection
In the program options
Banding types
Q, G and R, one model each
Classes
24 for the human karyotype, including X and Y
Outcome
Accuracy measured on the generated model
Comparison and trainingQ · G · R
ListKaryotypes verified by the laboratory
DatasetCreated on the workstation
Banding typeOne model for Q, G or R
Model generationElapsed time · estimated time

Model generated, accuracy measured.

Illustrative animation: not a screenshot of the program.

FIG. 02Neural network training panel: opening and creating the list, choice of banding (Q, G, R), Create dataset and Generate model.

04 Automatic model selection

The right model for each case, without changing settings.

The program chooses the model from the case identifier. Identifiers accept wildcards.

  • Several laboratories or protocols on the same workstation.
  • Each laboratory or protocol uses its own models.
  • The model follows the banding type of the case: Q, G or R.
Model selection
Laboratory A
Q, G and R models of laboratory A
Laboratory B
Q, G and R models of laboratory B
Other protocol
Models of that protocol

Illustrative animation: not a screenshot of the program.

Identifiers are defined with wildcards. The model chosen also depends on the banding type.

FIG. 03Karyotype proposed by the classifier: the operator can still edit it.

05 Data on the workstation and traceability

The images stay where they are. Every step is logged.

Dataset and model are built locally: the images stay on the workstation.

  • The creation of lists and datasets is written to the audit log.
  • Model generation is recorded, successful or failed; if successful, with the number of chromosomes and the accuracy.
  • Each line gives date, time, user, case and action.
  • The log is always written on the workstation.
DateTimeUserAction
Training list created
Training list opened
Dataset created
Model generated · chromosomes · accuracy
Model generation failed
Illustrative animation: not a screenshot of the program.1 file per day and workstation

06 Frequently asked questions

Questions about the classifier.

01Where do the images used for training stay?

On the workstation. The dataset and the model are built locally: the images stay on the laboratory’s computer.

02Can the automatic karyotype be corrected?

Yes. Automatic karyotyping is a suggestion: each chromosome can be moved, swapped, rotated and flipped by hand, and reclassified. The result is always checked by the operator.

03How long does it take to generate a model?

In internal tests a few minutes are enough, even with hundreds of karyotypes. This is an indication, not a guaranteed performance: the time depends on the computer and on the size of the list. During generation a bar shows the elapsed time and the estimated time, which refines itself with each generation.

04What accuracy can be achieved?

The program shows the measured accuracy for each model generated. It depends on the individual laboratory’s preparations and, in internal tests, grows with the number of karyotypes in the list: for this reason we do not quote percentages.

05Can different models be used for different protocols or laboratories?

Yes. The model is chosen automatically from the case identifier, also with wildcards. Several laboratories or protocols can work on the same workstation, each with its own models.

06Is a particular module needed?

The classifier is part of LeafYX automatic karyotyping. The licence modules, on a hardware key, are defined together with the laboratory: write to us from the Contact page.

07 Continue

Learn more.

For Research Use Only.

LeafYX is software for cytogenetics research. For Research Use Only (RUO): not a medical device and not for use in diagnostic procedures.

Automatic karyotyping produces a suggestion: the classification and layout of the chromosomes remain under the operator’s verification.

Demo

Evaluate the classifier on your own preparations.

Contact us for a LeafYX demonstration. We will show you the path from list to model and define together the modules best suited to your laboratory.