keras-team/keras-io
Feb 2026 – Feb 2026
1 Month active
Languages Used
Python
Technical Skills
Data VisualizationDeep LearningImage ProcessingKerasMachine LearningMedical Imaging
Mohammed Innat
PROFILE
Mohammed Innat
In February 2026, Innat Dev developed a 3D brain tumor segmentation pipeline and visualization demo for the keras-team/keras-io repository. Leveraging Python, TensorFlow, and Keras, Innat implemented end-to-end data loading, preprocessing, and model construction using SwinUNETR on BraTS MRI data. The work included region-level evaluation metrics to support detailed medical imaging analysis. Innat enhanced the demo with improved rendering and a GIF visualizer to better illustrate segmentation results, while also refining code examples for clarity and maintainability. This feature addressed the need for accurate, interpretable brain tumor segmentation to support diagnosis and treatment planning in medical imaging workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
12,256
Activity Months1
Work History
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 (keras-team/keras-io): Delivered a 3D brain tumor segmentation pipeline and enhanced visualization demo, leveraging BraTS MRI data and SwinUNETR. Implemented end-to-end data loading, preprocessing, model construction, and region-level evaluation metrics. Enhanced the demo with rendering improvements and a GIF visualizer for clearer demonstrations; performed typography and correctness fixes. Fixed rendering and ordering issues in the demo and refined code examples for clarity and maintainability.
2 Commits • 1 Features
Feb 1, 2026February 2026 (keras-team/keras-io): Delivered a 3D brain tumor segmentation pipeline and enhanced visualization demo, leveraging BraTS MRI data and SwinUNETR. Implemented end-to-end data loading, preprocessing, model construction, and region-level evaluation metrics. Enhanced the demo with rendering improvements and a GIF visualizer for clearer demonstrations; performed typography and correctness fixes. Fixed rendering and ordering issues in the demo and refined code examples for clarity and maintainability.
February 2026
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage50.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data VisualizationDeep LearningImage ProcessingKerasMachine LearningMedical ImagingTensorFlow
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