ARTIFICIAL INTELLIGENCE BASED MODEL FOR ESTABLISHING THE HISTOPATHOLOGICAL DIAGNOSTISTIC OF THE CUTANEOUS BASAL CELL CARCINOMA

  • Andrei Calin Dragomir George Emil Paalade University of Medicine, Pharmacy, Science and Technology of Targu Mures
  • Iuliu Gabriel Cocuz George Emil Paalade University of Medicine, Pharmacy, Science and Technology of Targu Mures
  • Ovidiu Simion Cotoi Department of Pathophysiology, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, Romania
  • Leonard Azamfirei Department of Anesthesia and Intensive Care, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, Romania
Keywords: histopathology, artificial intelligence, Mask-RCNN, cutaneous basal cell carcinoma

Abstract

Introduction: Artificial intelligence, a component of computer science, has the ability to process the multitude of medical data existing in the medical system around the world. The goal of our study is to build an Artificial Intelligence model, based on Machine Learning, capable of assisting pathologists around the world in the diagnosis of the basal cell carcinoma of the skin. Material and Method: Our study is represented by the development of an Mask-RCNN model, for the detection of cells with typical basal cell carcinoma tumoral changes. A number of 258 digitized histological images were used. The images emerged from Hematoxylin&Eosin stained pathology slides, diagnosed with cutaneous basal cell carcinoma between January 2018 and December 2021, at the Pathology Service of the Mureș County Clinical Hospital. Results: All the used images have the unique resolution of 2560x1920 pixels. For the learning process, we divided this images into two datasets: the learning dataset, representing 80% of the total images; and the test dataset, representing 20% of the total images. The AI ​​model was trained using 1000 epochs with a learning rate of 0.00025 and only one classification category: basal cell carcinoma. Conclusions: The AI model successfully identified in 85% of the cases the areas with pathological changes present in the input images

Published
2022-09-13
How to Cite
1.
Dragomir A, Cocuz I, Cotoi O, Azamfirei L. ARTIFICIAL INTELLIGENCE BASED MODEL FOR ESTABLISHING THE HISTOPATHOLOGICAL DIAGNOSTISTIC OF THE CUTANEOUS BASAL CELL CARCINOMA. amm [Internet]. 13Sep.2022 [cited 28Mar.2024];68(4). Available from: https://ojs.actamedicamarisiensis.ro/index.php/amm/article/view/174
Section
Original article