Multi-view content-based mammogram retrieval using dynamic similarity and locality sensitive hashing

作者：

Highlights：

• Introduction of the Multi-View Information Fusion (MVIF) in the Content-Based Mammogram Retrieval (CBMR) context.

• Assisting in radiological decision-making.

• Optimization of the computational time of retrieving relevant images using the coupled index based on a hashing technique.

• The imitation of the radiologists’ analyses using a dynamic similarity assessment.

摘要

•Introduction of the Multi-View Information Fusion (MVIF) in the Content-Based Mammogram Retrieval (CBMR) context.•Assisting in radiological decision-making.•Optimization of the computational time of retrieving relevant images using the coupled index based on a hashing technique.•The imitation of the radiologists’ analyses using a dynamic similarity assessment.

论文关键词：Multi-view information fusion,Multidimensional indexing,Locality sensitive hashing,Content-based mammogram retrieval,Dynamic similarity

论文评审过程：Received 23 January 2020, Revised 28 September 2020, Accepted 2 December 2020, Available online 13 December 2020, Version of Record 25 December 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107786