Skip to content
#

medical-imaging-segmentation

Star

Here are 3 public repositories matching this topic...

Language: All
Filter by language
All 3 Jupyter Notebook 2 Python 1

adilrasheed139 / Disentangled-Representation-Learning-for-Domain-Adaptation-in-Medical-Image-Segmentation

Star 1

Investigating DRL DCVAE} for mitigating 15% domain shift in cardiac MRI segmentation. Conclusively proves the Information Bottleneck trade-off: 0.02 generalization gap vs. 0.25 DSC performance. Structural limits of DRL identified for high-detail medical tasks.

python reproducible-research jupyter-notebook pytorch representation-learning variational-autoencoder domain-adaptation information-bottleneck feature-disentanglement adversarial-training domain-generalization conditional-variational-autoencoder generalization-gap medical-imaging-segmentation cardiovascular-imaging disentangled-representation-learning cardiac-mri-segmentation multi-vendor-data deep-learning-in-medicine content-utility-tradeoff
  • Updated Dec 20, 2025
  • Jupyter Notebook

tagorekanuri / Acute-Lymphoblastic-Leukemia-Detection

Star 0

Hybrid ML pipeline using FCM segmentation, EfficientNetB4 feature extraction, and XGBoost for leukemia detection.

python machine-learning deep-learning tensorflow kaggle medical-imaging xgboost fcm image-segmentation kaggle-dataset machine-learning-models xgboost-model machine-learning-projects xgboost-classifier medical-imaging-with-deep-learning medical-imaging-classification deep-learning-projects medical-imaging-segmentation leukemia-detection
  • Updated Dec 6, 2025
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the medical-imaging-segmentation topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the medical-imaging-segmentation topic, visit your repo's landing page and select "manage topics."

Learn more