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unet-tensorflow

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Breast cancer is one of the most common causes of death among women worldwide. Early detection helps reduce the number of premature deaths. In the study, I am working on creating a convolutional neural network capable of identifying tumor areas within medical images (which were taken with ultrasound).

  • Updated Jul 12, 2023
  • Jupyter Notebook

People with pulmonary disease often have a high opacity, which makes segmentation of the lung from chest X-rays more difficult. In this study, I propose a methodology to improve the performance of the U-NET structure so that it is able to extract the features and spatial characteristics of the X-ray images of the chest region.

  • Updated Jul 6, 2023
  • Jupyter Notebook

MultiPass U-Net is an advanced image segmentation model designed to iteratively refine predictions by running multiple passes through a U-Net architecture. Ideal for histopathology and medical imaging, it improves segmentation of fine structures and rare features by leveraging deep contextual learning across passes.

  • Updated Jun 29, 2025
  • Jupyter Notebook

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