Topic: "medicalimaging"
MMIV-ML/fastMONAI
Simplifying deep learning for medical imaging
Language: Jupyter Notebook - Size: 43.6 MB - Last synced at: 26 days ago - Pushed at: about 1 year ago - Stars: 98 - Forks: 17
REMEX-Lab/REMEX-Lab.github.io
REMEX Lab's home page.
Language: HTML - Size: 313 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 9 - Forks: 5
celilselcuk/Skin-Cancer-Detector
A CNN model to distinguish whether a skin lesion is malignant or benign: cancerous or not. Trained on 1500 images for both benign and malignant classes attained from the ISIC skin condition dataset with over 84% accuracy and 93 F1 score.
Language: Python - Size: 14.1 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 2 - Forks: 0
Islam-hady9/BrainTumorDetection-API
Brain Tumor Detection using CNN & FastAPI.
Language: Jupyter Notebook - Size: 61.8 MB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 2 - Forks: 0
amaljova/DicomDatabase
This script reads DICOM files in a source directory or in a list of source directories and searches for the patients in the given patients' list creates a DICOM DataBase in the destination directory, copies the files, and creates a DicomDataBase.csv file and a summary.txt file.
Language: Python - Size: 1.95 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0
Projects-Developer/Lung-Cancer-Detection-System-using-Machine-Learning
This project aims to develop a lung cancer detection system using machine learning techniques. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
Size: 5.86 KB - Last synced at: 5 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0
Michelle607/Pix2Pix
Using PIX2PIX for Synthesizing Computerized Tomographic Medical Images
Language: Python - Size: 146 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0
CodeByGirum/Chest-Xray-Pneumonia-Detection-Neural-Network-Model
This project aims to detect pneumonia from chest X-ray images using a Convolutional Neural Network (CNN). The model is trained on a dataset of chest X-ray images and evaluated for its performance. The project is ongoing, and I aim to fine-tune the model in the future. If you are seeing this, it means I am still working on the project.
Language: Jupyter Notebook - Size: 1020 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
DDILLOUD/Leukemia_Cell_Classification
Empowering healthcare with AI, LeukoVision automates the detection of leukemia cells in blood smear images. Revolutionizing leukemia care with speed and accuracy.
Language: Jupyter Notebook - Size: 4.42 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
vishal815/Team-LogicLegends-Proxmed-Hackathon-Hypodense-Segmentation-AI-Project-
Project Overview:- The objective of this hackathon challenge is to develop a robust and efficient algorithm or AI model capable of accurately segmenting the hypodense region from Brain Non-Contrast Computed Tomography (NCCT) images. The primary goal is to automate and streamline the identification of early ischemic changes in acute stroke patients.
Language: Jupyter Notebook - Size: 1.45 MB - Last synced at: 20 days ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
kathrin229/3d-transformer-med-classification
Repository for Master thesis project investigating classification of 3D chest CT scans using Vision Transformer.
Language: Python - Size: 7.8 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
rcali21/ENIGMA_DWI_Training
Repository containing files associated with ENIGMA diffusion weighted image preprocessing protocol and instructional video series. Designed by Ryan Cali for the 2022 ReproNim Fellowship Project and the Imaging Genetics Center at the University of Southern California. Questions? Reach out to the author: [email protected]
Language: Shell - Size: 1.44 GB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0
