PyTorch Implementation for Fracture Detection in Wrist Bone X-ray Images

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Deep Learning wrist-d
Overview

wrist-d

LICENSE

PWC
PyTorch Implementation for Fracture Detection in Wrist Bone X-ray Images

note:

Paper: Under Review at MPDI Diagnostics

Submission Date: November 12, 2021

abstract

It will be added after research paper accepted

Keywords: artificial intelligence; biomedical image processing; bone fractures; deep learning; fracture detection; object detection; transfer learning; wrist; X-ray

paper links

Paper: Under Review at MPDI Diagnostics

Preprint: https://arxiv.org/abs/2111.07355

Papers With Code: https://paperswithcode.com/paper/fracture-detection-in-wrist-x-ray-images

GitHub: https://github.com/fatihuysal88/wrist-d

authors

proposed detection models

models

proposed ensemble models

models

model performance

models

sample of wrist fracture results

models

Note: ground-truth bounding box (green), predicted bounding box (red)

requirements

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Comments
  • Transfer learning

    Transfer learning

    Hi, this is a brilliant work.

    I am working on object detection in chest X ray and would like to see if your model could be applied. But I have problem in running your code, may I know what is test.pyand ground_truth.json? I cannot find it. source code is: ''' !python ./tools/test.py {_model['config_path']} {_model['weight_path']} --format-only --options {a} ''' Also, it would be grateful if you could provide some guideline for using your models.

    Thank you.

    opened by ChakChiShing 0
Owner
Fatih UYSAL
PhD Candidate; Research Assistant at Gazi University
Fatih UYSAL
GitHub
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