Mammography classification with multi-view deep learning techniques: Investigating graph and transformer-based architectures-Reference-Cited by-同舟云学术

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Mammography classification with multi-view deep learning techniques: Investigating graph and transformer-based architectures

Published:2025-01 Issue: Volume:99 Page:103320
ISSN:1361-8415
Container-title:Medical Image Analysis
language:en
Short-container-title:Medical Image Analysis

Author:

Manigrasso Francesco^ORCID,Milazzo Rosario,Russo Alessandro Sebastian,Lamberti Fabrizio^ORCID,Strand Fredrik^ORCID,Pagnani Andrea^ORCID,Morra Lia^ORCID

Publisher

Elsevier BV

Reference72 articles.

1. Controlling the false discovery rate: a practical and powerful approach to multiple testing;Benjamini;J. R. Stat. Soc. Ser. B,1995

2. Transformer-based mass detection in digital mammograms;Betancourt Tarifa;J. Ambient Intell. Humaniz. Comput.,2023

3. The impact of mammographic screening on breast cancer mortality in Europe: A review of observational studies;Broeders;J. Med. Screen.,2012

4. Convolutional networks and transformers for mammography classification: An experimental study;Cantone;Sensors,2023

5. Automated analysis of unregistered multi-view mammograms with deep learning;Carneiro;IEEE Trans. Med. Imaging,2017

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