Pytorch implementation of the MICCAI 2020 paper SIMBA: Specific Identity Markers for Bone Age Assessment

Bone age estimation using hand X-Ray images

This is the Bone Age Assessment Dataset from RSNA Originally

Deep learning and segmentation in sex classification from left hand X-ray images in pediatric patients: how zero-shot Segment Anything Model (SAM) can improve medical image analysis

This is the Bone Age Assessment Dataset from Kaggle, But Enhanced by neu.ro

The project is a collaboration with David Loaiza ( 4th Yr Radiologist) from Mexico at Cardiology national institute "Ignacio Chavez". The aim is to estimate the bone age from the left hand radiographs. The model will be trained on a RSNA Pediatric Bone Age Challenge (2017) public dataset and evaluated on private dataset obtained from the hospital.

Final group project of "Human Data Analytics" course at University of Padova

Deeplasia bone age assessment service

Develop a deep learning-based model utilizing a fully connected convolutional neural network (CNN) to predict bone age from left-hand radiographs.