Medical-Heart-Segmentation-Application
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Updated
May 17, 2024 - Jupyter Notebook
Medical-Heart-Segmentation-Application
A microservice to expose a latent diffusion model for 3D Brain T1-weighted Image generation
Computer-Aided Diagnosis (CAD) Tool for frontotemporal dementia (FTD) based on Deep Learning and Explainable AI (MD3-Cam). The model uses 3D T1-weighted MRI brain scans. The paper has been published in Life journal.
Glioblastoma 3D Segmentation with nnU-Net and Patch Learning.
Leukocytes (WBCs) subtypes classification from blood smear images using Vision Transformers from Hugging Face and DenseNet artificial neural network from MONAI.
Created a semantic segmentation model using PyTorch framework called MONAI. In this project I have applied various data augmentation technique and have build a UNet deep learning model.
a robust liver segmentation model built using the UNet architecture and powered by the MONAI library, designed specifically for medical imaging tasks. this repository provides state-of-the-art tools for accurate liver segmentation in medical images.
monai_wholeBody_ct_segmentation
Project for creating synthetic tumor images from existing source images to train neural networks for lung tumor segmentation
Reimplementation of MONAI tutorials with W&B to run in Google Colab GPU
Brain Segmentation
AI powered segmentation of human organs from CT images
curriculum development ideas for computational biology internship and teaching assistantship @ AI4ALL
A collection of pre-built dataset classes for medical datasets.
cardiac segmentation
Semantic Segmentation of Spleen using UNET
Medical image augmentation tool that can be integrated with Pytorch & MONAI.
Generating attention maps from resnet50 and densenet using ACDC and EMIDEC dataset
Semantic segmentation and image-to-image translation based on AI
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