1. Development of automatic generation system for lung nodule finding descriptions.
- Author
-
Momoki Y, Ichinose A, Nakamura K, Iwano S, Kamiya S, Yamada K, and Naganawa S
- Subjects
- Humans, Artificial Intelligence, Tomography, X-Ray Computed methods, Lung, Radiologists, Radiographic Image Interpretation, Computer-Assisted methods, Lung Neoplasms diagnostic imaging, Solitary Pulmonary Nodule diagnostic imaging
- Abstract
Worldwide, lung cancer is the leading cause of cancer-related deaths. To manage lung nodules, radiologists observe computed tomography images, review various imaging findings, and record these in radiology reports. The report contents should be of high quality and uniform regardless of the radiologist. Here, we propose an artificial intelligence system that automatically generates descriptions related to lung nodules in computed tomography images. Our system consists of an image recognition method for extracting contents-namely, bronchopulmonary segments and nodule characteristics from images-and a natural language processing method to generate fluent descriptions. To verify our system's clinical usefulness, we conducted an experiment in which two radiologists created nodule descriptions of findings using our system. Through our system, the similarity of the described contents between the two radiologists (p = 0.001) and the comprehensiveness of the contents (p = 0.025) improved, while the accuracy did not significantly deteriorate (p = 0.484)., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: This research is a cooperative study between FUJIFILM Corporation and Nagoya University Graduate School of Medicine. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Momoki et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2024
- Full Text
- View/download PDF