Olivier Rukundo, Ph.D. (orukundo)

orukundo

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Company:Medical University of Vienna

Location:Austria

Home Page:https://sites.google.com/view/orukundo

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Olivier Rukundo, Ph.D.'s repositories

Cardiac-Ultrasound

Bicubic Interpolated Scan Conversion Vs Bilinear Interpolated Scan Conversion (Cardiac Ultrasound)

Edge-Enhancement-Fourier-Transform-

Edge Enhancement (Fourier Transform) is one of the topics presented during Kuopio Biomedical Image Analysis Center lecture series (see: https://www.youtube.com/watch?v=rBI17E086nQ). MATLAB code used for demonstration purposes is provided here:

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Automatic-MiniTEM-Image-Segmentation-

AI-based Tool used for Automatic Segmentation of Adenovirus in MiniTEM Images

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Edge-Enhancement-Convolution-

Edge Enhancement (Convolution) is one of the topics presented during Kuopio Biomedical Image Analysis Center lecture series (see: https://www.youtube.com/watch?v=jdK8Y-7mP5Y). MATLAB code used for demonstration purposes is provided here:

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generative-adversarial-networks

Generation of Synthetic Biomedical Images with Generative Adversarial Networks

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Implementation-of-interpolation-using-Spyder-IDE-Python-3.9-

Demonstration of basic image interpolation algorithms

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Instance-Segmentation

STEP 1 - Debugging Scripts for Binary and Labeled Mask Exports from .XML files

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Interpolated-Scan-Conversion-of-B-Mode-Cardiac-Ultrasound-Image-Sequences

Interpolated Scan Conversion of B-Mode Cardiac Ultrasound Image Sequences using different Interpolation Methods

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Median-Filter

Median filtering is one of the topics presented during Kuopio Biomedical Image Analysis Center lecture series (see: https://www.youtube.com/watch?v=Bl9XU30M8m4). MATLAB code used for demonstration purposes is provided here:

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Modified-USC-SIPI-Image-Database

Image dataset containing 210 Textures, Aerials, Miscellaneous, and Sequences images downloaded from the USC-SIPI Database. These images were resized to 512 × 512, 256 × 256, and 128 ×128, and converted to 8bits, using R2020a MATLAB software functions

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Semantic-Segmentation

Performing Semantic Segmentation of Histopathological Images | U-Net Implementation

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Tool-for-Evaluating-Deep-Learning-Models-in-Histopathological-Image-Analysis

Tool for Evaluating Deep Learning Models in Histopathological Image Analysis - A MATLAB-based User Interface [Tentative Version]

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U-NET-Semantic-Segmentation-of-Biomedical-Images-with-Pytorch-using-Spyder-IDE-Anaconda

Semantic Segmentation of Biomedical Images | Pytorch | Spyder IDE Anaconda

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