Implementation of DenseNet model on Standford's MURA dataset using PyTorch
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Updated
Jun 15, 2018 - Python
Implementation of DenseNet model on Standford's MURA dataset using PyTorch
Bone fracture detection using DenseNet on MURA dataset
Repo for Stanford's MURA Bone X-Ray Deep Learning Competition
Source code for Microsoft Code Fun Do Hackathon organized at IIT (BHU)
A Keras implementation of DenseNet model on Standford's MURA dataset
MURA (musculoskeletal radiographs) Deep Learning Project
An attempt at the Bone X-Ray Deep Learning Competition (Stanford ML Group).
Replicate MURA baseline and playing around
Abnormality Detection in Musculoskeletal Radiographs
Binary Classification into normal/abnormal X-rays of XR_SHOULDER of MURA dataset.
Fixes 500+ mislabeled MURA images
Analysis of Abnormality in Humerus X-Ray images using DenseNet
Implementation of Hough Transform for auto rotation of xray images
MuraMed is an innovative healthcare technology company that aims to revolutionize medical diagnostics with a focus on radiographs (X-Ray images). In the intricate landscape of today's healthcare, the company addresses the vital need for accurate, efficient, and swift diagnosis. MuraMed's specialization lies in detecting bone abnormalities.
implementing grabcut image segmentation on humerus xray images
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