Medical Image Captioning via Generative Pretrained Transformers

Autor:	Selivanov, Alexander, Rogov, Oleg Y., Chesakov, Daniil, Shelmanov, Artem, Fedulova, Irina, Dylov, Dmitry V.
Rok vydání:	2022
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	The automatic clinical caption generation problem is referred to as proposed model combining the analysis of frontal chest X-Ray scans with structured patient information from the radiology records. We combine two language models, the Show-Attend-Tell and the GPT-3, to generate comprehensive and descriptive radiology records. The proposed combination of these models generates a textual summary with the essential information about pathologies found, their location, and the 2D heatmaps localizing each pathology on the original X-Ray scans. The proposed model is tested on two medical datasets, the Open-I, MIMIC-CXR, and the general-purpose MS-COCO. The results measured with the natural language assessment metrics prove their efficient applicability to the chest X-Ray image captioning. Comment: 13 pages, 3 figures, The work was completed in 2021
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2209.13983 Zobrazit plný text záznamu View this record from Arxiv