Feature walk-through: Improved interaction between your classification/quantification models and the image data

Modeling and data analysis

  • Improved the interaction between models and image data, making easier to add new training data, retrain models and view the results on your image

    • Apply models on images directly in the Record Study table

    • Include, exclude or balance new training samples and then retrain models

    • Update categories and properties data from model prediction results

  • ONNX models inference performance improvements

  • Constrained spectral unmixing with new options for Scatter correction parameter "None" and method for "Sum To One Least Squares" Descriptors | Constrained-Spectral-Unmixing

  • Better naming for the different machine learning algorithms

  • More statistics in the classification confusion matrix (f-score, precision and recall)

  • Prediction summary (Observed vs Predicted) for quantification analysis through right-click in Table

  • Pre-treatment option to use SNV in the Explore tab

  • Use multiple spectral ranges for SAM (Spectral Angle Mapper) Spectral angle mapper (SAM) guide

  • Balance model with included train data or all train data

Image segmentation

  • Deep Learning Image Segmentation (Faster R-CNN and Yolo4/5) applied to pseudo RGB or model predicted image ONNX image segmentation

  • Image segmentation using YOLOv5

  • K-Means clustering as method for selecting representative spectrum Segmentations | Representative-spectrum

  • Add samples to Manual segmentation through right-click in Table

  • Object filter for segmentation (ex. object shape)

  • Summary table showing pixel overlap of multiple segmentations

  • Setting for Max number of objects in Deep Learning Image Segmentation

Visualization

  • Pixels on an object that are excluded in the segmentation (e.g. holes showing the background) are also excluded in the visualizations (Pixel Explore, Table thumbnail)

  • Merge all samples in segmentation now show all merged samples as one object in the preview image and in Table

  • Change RGB bands by right clicking on image

  • Test scan show % saturated bands

  • Selected samples in Pixel Explore can be highlighted in Table and vice versa

  • Option for Quantification model to predict and show value for individual pixels or only object average

  • Change direction of real time visualization (horizontal or vertical)

  • Option to show all or individual segmentation in Table if there are multiple segmentations on the same level

  • Select multiple samples in preview image by holding down the shift key and making rectangular selection of the area with the mouse

  • Yellow color for added class in Classification summary (confusion matrix)

Workflow 

  • Disable nodes in Analyse Tree that should not be used

  • Export and import Breeze models into your study

  • White and dark reference descriptor (signal intensity value)

  • Metadata descriptor for each image (ex. image length and resolution)

  • Delete workflow command in Breeze Runtime

  • Access Study settings in Analyse Tree on Measurement node

  • Link multiple segmentations to one output

Data acquisition

  • Stray light correction option in Settings 

  • Saturation descriptor for maximum value and percent saturated band per pixel

  • Explore pixel spectra on images in Test Scan

  • Indication that new white or dark reference will be taken when recording using reference cache

  • Set integration time in Record wizard

General ease-of-use improvements

  • Duplicate Study with option to include all measurements and data

  • Move measurement to another Group in the same Study