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Single shot detector application for image disease localization

Rushikesh Chopade, Aditya Stanam, View ORCID ProfileShrikant Pawar
doi: https://doi.org/10.1101/2021.09.21.461307
Rushikesh Chopade
1Department of Geology & Geophysics, Indian Institute of Technology, Kharagpur, India
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Aditya Stanam
2Department of Toxicology, University of Iowa, Iowa City, Iowa 52242-5000, USA
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Shrikant Pawar
3Yale Center for Genomic Analysis, Yale School of Medicine, Yale University, New Haven, Connecticut, 30303, USA
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  • ORCID record for Shrikant Pawar
  • For correspondence: shrikant.pawar@yale.edu
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Abstract

Bounding box algorithms are useful in localization of image patterns. Recently, utilization of convolutional neural networks on X-ray images has proven a promising disease prediction technique. However, pattern localization over prediction has always been a challenging task with inconsistent coordinates, sizes, resolution and capture positions of an image. Several model architectures like Fast R-CNN, Faster R-CNN, Histogram of Oriented Gradients (HOG), You only look once (YOLO), Region-based Convolutional Neural Networks (R-CNN), Region-based Fully Convolutional Networks (R-FCN), Single Shot Detector (SSD), etc. are used for object detection and localization in modern-day computer vision applications. SSD and region-based detectors like Fast R-CNN or Faster R-CNN are very similar in design and implementation, but SSD have shown to work efficiently with larger frames per second (FPS) and lower resolution images. In this article, we present a unique approach of SSD with a VGG-16 network as a backbone for feature detection of bounding box algorithm to predict the location of an anomaly within chest X-ray image.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Authors: Aditya Stanam, E-mail: aditya-stanam{at}uiowa.edu, Rushikesh Chopade, E-mail: rushikeshchopaderc{at}gmail.com

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted September 24, 2021.
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Single shot detector application for image disease localization
Rushikesh Chopade, Aditya Stanam, Shrikant Pawar
bioRxiv 2021.09.21.461307; doi: https://doi.org/10.1101/2021.09.21.461307
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Single shot detector application for image disease localization
Rushikesh Chopade, Aditya Stanam, Shrikant Pawar
bioRxiv 2021.09.21.461307; doi: https://doi.org/10.1101/2021.09.21.461307

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