New thyroid scintigraphy datasets: Construction and benchmark assessment in diagnosis of residual thyroid tissue

  • Minh Lại School of Electrical and Electronics Engineering, Hanoi University of Science and Technology
  • Nguyen Chi Thanh Military Information Technology Institute, Academy of Military Science and Technology
  • Hai Phung Nhu Military Information Technology Institute, Academy of Military Science and Technology
  • Dang Nam Thang Medical Equipment of Department, 108 Medical Central Hospital
  • Trung Nguyen Thanh Medical Equipment of Department, 108 Medical Central Hospital
  • Chu Minh Duc Nuclear Medicine of Department, 108 Medical Central Hospital
  • Ha Nguyen Thai School of Electrical and Electronics Engineering, Hanoi University of Science and Technology
  • Nguyen Duc Thuan School of Electrical and Electronics Engineering, Hanoi University of Science and Technology
Keywords: SPECT image; Thyroid scintigraphy; Computer-Aided Diagnosis; Residual thyroid tissue; Transfer learning.

Abstract

Thyroid scintigraphy, a type of single photon emission computed tomography (SPECT) imaging technique that uses radioactive isotopes to capture images of the thyroid gland, helps detect thyroid abnormalities and diagnosing thyroid cancer. A promising research direction for machine learning applications to assist in diagnosis. Most algorithms for detecting and predicting uptake in the thyroid region rely on proprietary or published datasets with unspecified information. This makes comparing the performance among different methods and developing solutions for various problems challenging. To address this issue, we have constructed two standardized datasets of thyroid scintigraphy images for identifying and quantifying the depth. The purpose of designing the models is to establish a benchmark assessment for developing CADx models on the datasets in the future.

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Published
2023-06-25
Issue
Vol. 88 (2023)
Section
Overview