1. Generating and evaluating synthetic data in digital pathology through diffusion models.
- Author
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Pozzi M, Noei S, Robbi E, Cima L, Moroni M, Munari E, Torresani E, and Jurman G
- Subjects
- Humans, Image Processing, Computer-Assisted methods, Pathology, Clinical methods, Reproducibility of Results, Deep Learning
- Abstract
Synthetic data is becoming a valuable tool for computational pathologists, aiding in tasks like data augmentation and addressing data scarcity and privacy. However, its use necessitates careful planning and evaluation to prevent the creation of clinically irrelevant artifacts.This manuscript introduces a comprehensive pipeline for generating and evaluating synthetic pathology data using a diffusion model. The pipeline features a multifaceted evaluation strategy with an integrated explainability procedure, addressing two key aspects of synthetic data use in the medical domain.The evaluation of the generated data employs an ensemble-like approach. The first step includes assessing the similarity between real and synthetic data using established metrics. The second step involves evaluating the usability of the generated images in deep learning models accompanied with explainable AI methods. The final step entails verifying their histopathological realism through questionnaires answered by professional pathologists. We show that each of these evaluation steps are necessary as they provide complementary information on the generated data's quality.The pipeline is demonstrated on the public GTEx dataset of 650 Whole Slide Images (WSIs), including five different tissues. An equal number of tiles from each tissue are generated and their reliability is assessed using the proposed evaluation pipeline, yielding promising results.In summary, the proposed workflow offers a comprehensive solution for generative AI in digital pathology, potentially aiding the community in their transition towards digitalization and data-driven modeling., Competing Interests: Declaration of generative AI in scientific writing During the preparation of this work the authors used ChatGPT3.5 for grammar and spelling checks, as well as rephrasing to enhance readability. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)
- Published
- 2024
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