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marekkoc/README.md

Hi!

I'm a researcher and software developer specializing in computer science, data science, computer vision, and 2D/3D visualization, with extensive experience in AI, machine learning, and deep learning. Proficient in Python, C++, Matlab and R, with academic expertise as an Assistant Professor. I excel at leading multidisciplinary projects, fostering collaboration across diverse teams, and mentoring students in technical domains. With a passion for electronics, robotics, drones, and smart homes, I'm looking to apply my academic knowledge in practical industry environments. My repositories showcase implementations of visualization techniques, data processing algorithms, AI models, and computer vision solutions.

About me and project arvhive,

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  1. geometric-blood-vessels-modeling geometric-blood-vessels-modeling Public

    Proposed methods provide objective, accurate geometrical information on blood vessel trees. Potentially can be used for noninvasive blood flow simulation in critical regions and support the constru…

  2. EndoMR-TextureAnalysis EndoMR-TextureAnalysis Public

    A repository for texture-based analysis of MR images in endometrial carcinoma classification. Implements extraction of texture features from pharmacokinetic parameter maps derived from DCE-MRI, ADC…

    1

  3. MCI-to-AD-Conversion-Predictors MCI-to-AD-Conversion-Predictors Public

    Machine learning models predicting conversion from Mild Cognitive Impairment to Alzheimer's Disease using baseline clinical data and FAQ informant reportsfrom ADNI dataset

    Jupyter Notebook

  4. 2d-3d-unet-skullstripping 2d-3d-unet-skullstripping Public

    2D and 3D U-Net models for automated skull stripping in brain MRI. Covers methodology, results, and performance of deep learning approaches using fastai on heterogeneous MRI datasets.

    Jupyter Notebook

  5. MMIV-ML/KidneySegm MMIV-ML/KidneySegm Public

    Kidney segmentation in MR images: data and code examples

    Jupyter Notebook

  6. vascular-tree-3D-texture-analysis vascular-tree-3D-texture-analysis Public

    Quantitative analysis of 3D vascular tree images using texture features. Implementation of methods for classifying blood vessel structures and monitoring physical parameters using 3D co-occurrence …