Bag of Tricks of Hybrid Network for Covid-19 Detection of CT Scans

Chih Chung Hsu, Chih Yu Jian, Chia Ming Lee, Chi Han Tsai, Shen Chieh Tai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a study using deep learning models to analyze lung Computed Tomography (CT) images. Traditionally used for this task, deep learning frameworks face compatibility issues due to the variances in CT image slice numbers and resolutions caused by the use of different machines. Typically, individual slices are predicted and combined to obtain the final result, but this approach lacks slice-wise feature learning and ultimately leads to decreased performance. To address this limitation, we propose a novel slice selection method for each CT dataset, effectively filtering out uncertain slices and enhancing the model's performance. Moreover, we introduce a spatial-slice feature learning technique that uses a conventional and efficient backbone model for slice feature training. We then extract one-dimensional data from the trained COVID and non-COVID classification models by employing a dedicated classification model. Leveraging these experimental steps, we integrate one-dimensional features with multiple slices for channel merging and employ a 2D convolutional neural network for classification. In addition to the aforementioned methods, we explore various high-performance classification models, ultimately achieving promising results.

Original languageEnglish
Title of host publicationICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350302615
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, ICASSPW 2023 - Rhodes Island, Greece
Duration: 2023 Jun 42023 Jun 10

Publication series

NameICASSPW 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, Proceedings

Conference

Conference2023 IEEE International Conference on Acoustics, Speech and Signal Processing Workshops, ICASSPW 2023
Country/TerritoryGreece
CityRhodes Island
Period23-06-0423-06-10

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Acoustics and Ultrasonics
  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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