A Novel Single Continuous Shot Multiple Lesions Endoscopy Report Generation

Automatic Report Generation(ARG), which aims to automatically provide observations on images, is challenged by the lack of coherence between multiple scenes and precise description of multiple lesions. In order to explore the task of multi-scene multi-lesion report generation(MSMLRG) in one shot, in this paper, we introduce a multi-scene multi-lesion report generation framework to extract the scene-report alignment relation and scene-topic relation. Specifically, we design a scene-report feature aligner to achieve fine-grained alignment of different lesion in different scenes in images and reports, and incorporate a topic-aware module to help generate a topic text vocabulary for different scenes. Our framework has been successfully experimented on several automatic report generation models, and performs well on automatic evaluation metrics. The framework for one-shot report generation during multi-scene not only fills the gap of multi-scene image report generation, but also effectively improves the accuracy and consistency of diagnostic reports.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10888634
Citations
3
Primary Topic
Esophageal Cancer Research and Treatment
Type
article
Field-Weighted Citation Impact
6.02

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article

A Novel Single Continuous Shot Multiple Lesions Endoscopy Report Generation

Liujie Hua, Junhua Kuang, Xinpan Yuan, Guihu Zhao et al.
3 citations
Esophageal Cancer Research and Treatment
6.02
article

A Novel Single Continuous Shot Multiple Lesions Endoscopy Report Generation

Liujie Hua, Junhua Kuang, Xinpan Yuan, Guihu Zhao, Jiabao Li, Changhong Zhang
article en
3 citations

Abstract

Automatic Report Generation(ARG), which aims to automatically provide observations on images, is challenged by the lack of coherence between multiple scenes and precise description of multiple lesions. In order to explore the task of multi-scene multi-lesion report generation(MSMLRG) in one shot, in this paper, we introduce a multi-scene multi-lesion report generation framework to extract the scene-report alignment relation and scene-topic relation. Specifically, we design a scene-report feature aligner to achieve fine-grained alignment of different lesion in different scenes in images and reports, and incorporate a topic-aware module to help generate a topic text vocabulary for different scenes. Our framework has been successfully experimented on several automatic report generation models, and performs well on automatic evaluation metrics. The framework for one-shot report generation during multi-scene not only fills the gap of multi-scene image report generation, but also effectively improves the accuracy and consistency of diagnostic reports.

Central South University (CN), Zhuzhou Central Hospital (CN), Xiangya Hospital Central South University (CN), Hunan University of Technology (CN)
Education Department of Hunan Province, Natural Science Foundation of Hunan Province, Research and Innovation Foundation
Openalex Percentile: Top 5%
Esophageal Cancer Research and Treatment
6.02
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A Novel Single Continuous Shot Multiple Lesions Endoscopy Report Generation — Liujie Hua, Junhua Kuang, et al. · (2025) | TGRS Research Map | TGRS