AI-Based Method for Thyroid Cancer in Histopathology Imaging: Insights and Challenges
Nabila Husna Shabrina, Dadang Gunawan, Agnes Stephanie Harahap, Maria Francisca Ham · 2024
The global incidence of thyroid cancer has increased over the past three decades, making it the seventh most common cancer worldwide. Conventional histopathology, the gold standard for diagnosing cancer, has limitations such as timeconsuming manual processes and inconsistencies between experts. Digital and computer-aided Pathology have emerged to address these limitations, and recent advancements in Artificial Intelligence have facilitated their use. This paper presents a systematic literature review investigating the current state of AIbased methods for diagnosing thyroid cancer using histopathological images. Three critical questions guided the review, focusing on image processing and classification methods currently used for identifying thyroid cancer in histopathological images, as well as the dataset utilized for conducting this research. This systematic review revealed essential information on the current trends and challenges of AI-based methods for thyroid cancer histopathology images.