Research map: DBT_DCNN: a new convolutional neural network for mass detection in digital breast tomosynthesis

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  17. Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography · Ravi K. Samala · 2016 · 290 citations · Cited by this paper
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  19. Breast cancer screening with tomosynthesis (3D mammography) with acquired or synthetic 2D mammography compared with 2D mammography alone (STORM-2): a population-based prospective study · Daniela Bernardi · 2016 · 279 citations · Cited by this paper
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  22. Breast Cancer Diagnosis in Digital Breast Tomosynthesis: Effects of Training Sample Size on Multi-Stage Transfer Learning Using Deep Neural Nets · Ravi K. Samala · 2018 · 240 citations · Cited by this paper
  23. Consequences of False-Positive Screening Mammograms · Anna N.A. Tosteson · 2014 · 223 citations · Cited by this paper
  24. Systematic review of the psychological consequences of false-positive screening mammograms · Mark Bond · 2013 · 185 citations · Cited by this paper
  25. One-view breast tomosynthesis versus two-view mammography in the Malmö Breast Tomosynthesis Screening Trial (MBTST): a prospective, population-based, diagnostic accuracy study · Sophia Zackrisson · 2018 · 182 citations · Cited by this paper
  26. Performance of breast cancer screening using digital breast tomosynthesis: results from the prospective population-based Oslo Tomosynthesis Screening Trial · Per Skaane · 2018 · 129 citations · Cited by this paper
  27. Dedicated breast computed tomography: Basic aspects · Antonio Sarno · 2015 · 124 citations · Cited by this paper
  28. Radiologist Characteristics Associated With Interpretive Performance of Diagnostic Mammography · Diana L. Miglioretti · 2007 · 107 citations · Cited by this paper
  29. Mass detection in digital breast tomosynthesis data using convolutional neural networks and multiple instance learning · Mina Yousefi · 2018 · 102 citations · Cited by this paper
  30. Cost effectiveness of the NHS breast screening programme: life table model · Paul D.P. Pharoah · 2013 · 86 citations · Cited by this paper
  31. Concurrent Computer-Aided Detection Improves Reading Time of Digital Breast Tomosynthesis and Maintains Interpretation Performance in a Multireader Multicase Study · Richard A. Benedikt · 2017 · 71 citations · Cited by this paper
  32. Improving digital breast tomosynthesis reading time: A pilot multi-reader, multi-case study using concurrent Computer-Aided Detection (CAD) · Corinne Balleyguier · 2017 · 58 citations · Cited by this paper
  33. Dedicated breast CT: state of the art—Part II. Clinical application and future outlook · Yueqiang Zhu · 2021 · 54 citations · Cited by this paper
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  35. A randomized controlled trial of digital breast tomosynthesis versus digital mammography in population-based screening in Bergen: interim analysis of performance indicators from the To-Be trial · Hildegunn Siv Aase · 2018 · 49 citations · Cited by this paper
  36. Diagnostic performance of digital breast tomosynthesis with a wide scan angle compared to full-field digital mammography for the detection and characterization of microcalcifications · Paola Clauser · 2016 · 46 citations · Cited by this paper
  37. Latent feature representation with 3-D multi-view deep convolutional neural network for bilateral analysis in digital breast tomosynthesis · Dae Hoe Kim · 2016 · 43 citations · Cited by this paper
  38. A deep learning classifier for digital breast tomosynthesis · Roberta Ricciardi · 2021 · 43 citations · Cited by this paper
  39. Detection of soft tissue densities from digital breast tomosynthesis: comparison of conventional and deep learning approaches · Sergei V. Fotin · 2016 · 40 citations · Cited by this paper

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