IJCAI2020 & IJCV2021 🌇 Unsupervised Scene Adaptation with Memory Regularization in vivo

• UpdatedOct 24, 2025
• Python

Building an ACL tear detector to spot knee injuries from MRIs with PyTorch (MRNet)

• UpdatedApr 15, 2021
• Python

Code for CVPR 2021 paper. "Learning Calibrated Medical Image Segmentation via Multi-rater Agreement Modeling".

• UpdatedApr 5, 2023
• Python

🛠 Licence plate detection and recognition tool. A new lightweight tool is able to recognize license plates in real time on devices with significant limitations in computing power.

• UpdatedJun 3, 2023
• Python

[CMIG 2022 / MIDL 2021] Official implementation of the MRPyrNet architecture proposed in the papers "Improving MRI-based Knee Disorder Diagnosis with Pyramidal Feature Details" (MIDL 2021) and "Deep convolutional feature details for better knee disorder diagnoses in magnetic resonance images" (Computerized Medical Imaging and Graphics, 2022).

• UpdatedNov 23, 2022
• Python

Building an ACL tear , Meniscus tear and Knee abnormality detector to spot knee injuries from MRIs with PyTorch (MRNet)

• UpdatedSep 13, 2024
• JavaScript

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

• UpdatedAug 20, 2020
• Jupyter Notebook

• UpdatedJun 24, 2020
• Jupyter Notebook

Deep Learning Based Diagnosis, Abnormality and Common Disorders detection using Knee MRI Stanford MRNet Dataset

• UpdatedMar 3, 2022
• Jupyter Notebook

A Knee MRI Dataset And Competition - Stanford Competition with MRI Dataset on knee injuries

• UpdatedApr 16, 2020

Implementation of the MRNet model proposed in the paper "Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet" for knee disorders diagnosis.

• UpdatedJul 31, 2020
• Python

Machine Learning project using python. detect the patient suffering from (abnormal OR ACL OR maniacal tears)from a different angles (Axial, Coronal, sagittal) and print the accuracy of this detect. Build a deep CNN model to perform the classification. Use Transfer Learning and ensemble. Plot accuracy, F-score, and loss of both training and valid…

• UpdatedMay 28, 2019
• Jupyter Notebook

This is an assignment for Pattern Recognition Course taught at Alexandria University, Faculty of Engineering offered in Spring 2019. Our Official Contribution on developing a Model for MRNet dataset.

• UpdatedJul 19, 2019
• Jupyter Notebook