research-article

Medical Image Classification based on an Adaptive Size Deep Learning Model

Authors:

Gautam SrivastavaAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 17, Issue 3s

Article No.: 102, Pages 1 - 18

https://doi.org/10.1145/3465220

Published: 26 October 2021 Publication History

Abstract

With the rapid development of Artificial Intelligence (AI), deep learning has increasingly become a research hotspot in various fields, such as medical image classification. Traditional deep learning models use Bilinear Interpolation when processing classification tasks of multi-size medical image dataset, which will cause the loss of information of the image, and then affect the classification effect. In response to this problem, this work proposes a solution for an adaptive size deep learning model. First, according to the characteristics of the multi-size medical image dataset, the optimal size set module is proposed in combination with the unpooling process. Next, an adaptive deep learning model module is proposed based on the existing deep learning model. Then, the model is fused with the size fine-tuning module used to process multi-size medical images to obtain a solution of the adaptive size deep learning model. Finally, the proposed solution model is applied to the pneumonia CT medical image dataset. Through experiments, it can be seen that the model has strong robustness, and the classification effect is improved by about 4% compared with traditional algorithms.

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Index Terms

Medical Image Classification based on an Adaptive Size Deep Learning Model
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations
        Image representations

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 17, Issue 3s

October 2021

324 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/3492435

Editor:
Alberto Del Bimbo
University of Firenze, Italy

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2021

Accepted: 01 May 2021

Revised: 01 April 2021

Received: 01 November 2020

Published in TOMM Volume 17, Issue 3s

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Funding Sources

Natural Science Foundation of Hunan Province
Key Scientific Research Projects of Department of Education of Hunan Province
Hunan Provincial Science & Technology Project Foundation
National Natural Science Foundation of China
Scientific Research Fund of Hunan Provincial Education Department

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