[Cross-modal hash retrieval of medical images based on Transformer semantic alignment].

ABSTRACT: Medical cross-modal retrieval aims to achieve semantic similarity search between different modalities of medical cases, such as quickly locating relevant ultrasound images through ultrasound reports, or using ultrasound images to retrieve matching reports. However, existing medical cross-modal hash retrieval methods face significant challenges, including semantic and visual differences between modalities and the scalability issues of hash algorithms in handling large-scale data. To address these challenges, this paper proposes a Medical image Semantic Alignment Cross-modal Hashing based on Transformer (MSACH). The algorithm employed a segmented training strategy, combining modality feature extraction and hash function learning, effectively extracting low-dimensional features containing imp

SUBMITTER: Wu Q 

PROVIDER: S-EPMC11955336 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature