Aphelion Extensions

Deep Learning extensions for Aphelion Imaging Software Suite

With this new Aphelion extensions, there is no need to be a programmer to develop an algorithm based on Artificial Intelligence (AI). The Deep Learning extensions compatible with the Aphelion Imaging Software Suite help the user to develop an Artificial Intelligence application without having to be an expert in the field.

The first step of the development of an AI application involves collecting data to be used to train the Deep Learning system. Thanks the Annotate software product, fully compatible with the Aphelion Imaging Software Suite, highly configurable to be adapted to the specific annotation process, the user can seamlessly and quickly annotate images and videos. Annotated data are then used to train the Convolutional Neural Network (CNN).

The second step is the training process. This step is not straightforward as it requires an expertise in Deep Learning. It involves first splitting the set of annotated data into two sets: A training dataset and an evaluation dataset, second selecting the best CNN architecture, third generating the model, and fourth providing the classification result and the evaluation report. To help the user and save time, ADCIS can take in charge this task. Contact ADCIS to learn more about this offer.

3D Image Processing & 3D Image Display Extensions

Process, Analyze, and Display 3D Images
Aphelion™ users can now effectively process and display 3D images using virtually the same processing and analysis power provided for 2D images. The Aphelion Imaging Software Suite includes two optional extensions for these functions: the 3D Image Display Extension and the 3D Image Processing Extension. Using these powerful extensions, images acquired from sensor devices such as X-ray Micro-CT, 3D Atom Probe, confocal microscopes, medical scanners, and other 3D devices, can be easily processed, analyzed, and displayed using the Aphelion Dev Graphical User Interface.

The Aphelion 2D image processing operators have been enhanced to handle 3D data including, for example, convolution, addition, subtraction, maximum, erosion, dilation, distance function, labeling, watershed, and threshold. The 3D Image Processing Extension includes analysis on 3D images and true 3D Objectsets. A set of specific 3D measurements is available such as sphericity, surface area, and volume.

POWERFUL SOFTWARE BASED ON SUPERVISED CLASSIFICATION TECHNOLOGY TO EFFICIENTLY CLASSIFY OBJECTS OF INTEREST
Classifying Objects in Images
The Aphelion™ Imaging Software Suite includes four powerful tools for developing advanced classification applications for automatically identifying the type or class of objects found in a set of images. The four tools are Classifier Builder (the classification application front-end) and three classifier extensions: Fuzzy Logic, Neural Network Toolkit, and Random Forest, with the last two being an optional Aphelion extension product.

Classifier Builder
Classifier Builder, a tool included with the Aphelion Dev product, serves as a front-end for a classification application. It is used to define training data and to configure a classifier tool through a supervised learning process performed on a training dataset. With ClassifierBuilder, the user can easily and seamlessly perform a manual classification that assigns objects of interest to user-defined classes. This is especially useful for creating a training dataset. The ClassifierBuilder modifies ObjectSets in the sense it is adding a new attribute to each object that will contain the object’s class.

ClassifierBuilder includes capabilities to:

Load ObjectSets in a classification project
Define object classes
Select object measurements to compute
Select attributes to use during the training process
Compute classifier parameters automatically
Perform a manual classification
 

The Classifier Builder is provided with the Fuzzy Logic classifier extension (Fuzzy Logic) to enable the user to quickly perform object classification based on fuzzy logic. As an option, the Neural Network classifier can be used for more advanced classification tasks (Neural Network Toolkit).