Retina-Match: Ipsilateral Mammography Lesion Matching in a Single Shot Detection Pipeline

Conference Paper

In mammography and tomosynthesis, radiologists use the geometric relationship of the four standard screening views to detect breast abnormalities. To date, computer aided detection methods focus on formulations based only on a single view. Recent multi-view methods are either black box approaches using methods such as relation blocks, or perform extensive, case-level feature aggregation requiring large data redundancy. In this study, we propose Retina-Match, an end-to-end trainable pipeline for detection, matching, and refinement that can effectively perform ipsilateral lesion matching in paired screening mammography images. We demonstrate effectiveness on a private, digital mammography data set with 1,016 biopsied lesions and 2,000 negative cases.

Full Text

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Duke Authors

Cited Authors

Ren, Y; Lu, J; Liang, Z; Grimm, LJ; Kim, C; Taylor-Cho, M; Yoon, S; Marks, JR; Lo, JY

Published Date

January 1, 2021

Published In

Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume / Issue

12905 LNCS /

Start / End Page

345 - 354

Electronic International Standard Serial Number (EISSN)

1611-3349

International Standard Serial Number (ISSN)

0302-9743

International Standard Book Number 13 (ISBN-13)

9783030872397

Digital Object Identifier (DOI)

10.1007/978-3-030-87240-3_33

Citation Source

Scopus

Scholars@Duke