Evaluating Urine Cytology Slide Digitization Efficiency: A Comparative Study Using an Artificial Intelligence-Based Heuristic Scanning Simulation and Multiple Z-Plane Scanning.

Journal: Acta cytologica
PMID: 38648759

Abstract

INTRODUCTION: Digitizing cytology slides presents challenges because of their three-dimensional features and uneven cell distribution. While multi-Z-plane scan is a prevalent solution, its adoption in clinical digital cytopathology is hindered by prolonged scanning times, increased image file sizes, and the requirement for cytopathologists to review multiple Z-plane images.

Authors

  • Jen-Fan Hang
    Division of Cytopathology, Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Yen-Chuan Ou
    Division of Urology, Department of Surgery, Taichung Veterans General Hospital, Taichung, Taiwan, R.O.C. Division of Urology, Department of Surgery, Tungs' Taichung MetroHarbor Hospital, Taichung, Taiwan, R.O.C. School of Medicine, National Yang-Ming University, Taipei, Taiwan, R.O.C. ycou228@gmail.com.
  • Wei-Lei Yang
    AIxMed, Inc, Santa Clara, California, USA.
  • Tang-Yi Tsao
    Department of Pathology, Tung's Taichung MetroHarbor Hospital, Taichung, Taiwan.
  • Cheng-Hung Yeh
    AIxMed, Inc, Santa Clara, California, USA.
  • Chi-Bin Li
    AIxMed, Inc., Santa Clara, California, USA.
  • En-Yu Hsu
    AIxMed, Inc., Santa Clara, California, USA.
  • Po-Yen Hung
    AIxMed, Inc., Santa Clara, California, USA.
  • Ming-Yu Lin
    AIxMed, Inc, Santa Clara, California, USA.
  • Yi-Ting Hwang
    Department of Statistics, National Taipei University, Taipei, Taiwan.
  • Tien-Jen Liu
    AIxMed, Inc, Santa Clara, California, USA.
  • Min-Che Tung
    Division of Urology, Department of Surgery, Tung's Taichung MetroHarbor Hospital, Taichung, Taiwan.

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