Fine-Grained Image-Text Alignment in Medical Imaging Enables Explainable Cyclic Image-Report Generation
Wenting Chen, Linlin Shen, Jingyang Lin, Jiebo Luo, Xiang Li, Yixuan Yuan
Abstract
Fine-grained vision-language models (VLM) have been widely used for inter-modality local alignment between the predefined fixed patches and textual words. However, in medical analysis, lesions exhibit varying sizes and positions, and using fixed patches may cause incomplete representations of lesions. Moreover, these methods provide explainability by using heatmaps to show the general image areas potentially associated with texts rather than specific regions, making their explanations not explicit and specific enough. To address these issues, we propose a novel Adaptive patchword Matching (AdaMatch) model to correlate chest X-ray (CXR) image regions with words in medical reports and apply it to CXRreport generation to provide explainability for the generation process. AdaMatch exploits the fine-grained relation between adaptive patches and words to provide explanations of specific image regions with corresponding words. To capture the abnormal regions of varying sizes and positions, we introduce an Adaptive Patch extraction (AdaPatch) module to acquire adaptive patches for these regions adaptively. Aiming to provide explicit explainability for the CXR-report generation task, we propose an AdaMatch-based bidirectional LLM for Cyclic CXR-report generation (AdaMatch-Cyclic). It employs AdaMatch to obtain the keywords for CXR images and 'keypatches' for medical reports as hints to guide CXR-report generation. Extensive experiments on two publicly available CXR datasets validate the effectiveness of our method and its superior performance over existing methods. CXR Image Ground-truth R2GenCMN AdaMatch-Cyclic Keywords Small calcification right lung base with appearance of old granulomatous disease. Also small perihilar calcified lymph XXXX. Lungs are clear. No active parenchymal disease. No XXXX of pleural effusions. No pulmonary edema. Normal heart size. No XXXX of active cardiopulmonary disease. Unchanged. Heart size is normal. The mediastinal and hilar contours are normal. The pulmonary vasculature is normal. Lungs are clear. No pleural effusion or pneumothorax is seen. There are no acute osseous abnormalities. No acute cardiopulmonary abnormality. The trachea is midline. The heart is normal in size. The mediastinum is unremarkable. Mild granulomatous sequela are noted. The lungs are grossly clear. There is no pneumothorax. No acute disease.
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Install the CLIlune papers fulltext 1aa414b2-5e2a-4e70-ba5a-2c5d49d4c1c6Cited by top-tier papers3
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- Enhanced Contrastive Learning with Multi-view Longitudinal Data for Chest X-ray Report GenerationKang Liu, Zhuoqi Ma, Xiaolu Kang, Yunan Li et al.CVPR 2025
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