Brain Tumor Localization Application

Customer

Datazo InfoTech has developed a solution for the healthcare industry aimed at improving automated brain cancer diagnostics by applying convolutional neural network (CNN) algorithms.

Loren Huguean

/ CTO – EU-Based Company

Datazo InfoTech developed an AI-based application for brain MRI scans analysis. Using the convolutional neural network (CNN) algorithms, the application helps doctors localize brain tumors, plan surgeries and track the treatment progress.

Client	Sweden-based Company
Tags	basic
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Requirements

Our solution

The automated medical diagnostics application was to analyze uploaded brain MRI scans and mark the scanned area with the segmented tumor, including each tissue type defined – normal tissue, edema, non-enhancing core, necrotic core and enhancing core.

The project stages included building a specific CNN structure; preparing training and testing datasets; training and testing the CNN, and evaluating accuracy. ScienceSoft’s team of senior C++ engineers created a CNN structure with the following layers:
5 convolutional layers
1 ReLU activation layer
1 pooling layer
1 fully connected layer

The MRI analysis process included:

Segmentation of 3 planes - XY, XZ and YZ
Application of 3 post-processing filters to remove noise and other artifacts
Merging of 3 output files into one
Application of the final post-processing filter to the merged file

To evaluate CNN performance, the team compared acquired results with the ground truth. The ground truth was taken from BRATS imaging datasets, which have been segmented and annotated manually by one to four raters as well as approved by neuro-radiologists. The maximum network accuracy achieved is 83.36%.

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Results:

Datazo InfoTech developed a CNN-based application to automatically analyze brain MRI scans, localize tumors and define each tissue type. The application allows to assist health specialists in brain cancer diagnostics, surgery planning and treatment progress tracking.