Breast pectoral muscle segmentation in mammograms using a modified holistically-nested edge detection network

Andrik Rampun, Karen López-Linares, Philip J. Morrow, Bryan W. Scotney, Hui Wang, Inmaculada Garcia Ocaña, Grégory Maclair, Reyer Zwiggelaar, Miguel A. González Ballester, Iván Macía

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

63 Dyfyniadau(SciVal)
352 Wedi eu Llwytho i Lawr (Pure)


This paper presents a method for automatic breast pectoral muscle segmentation in mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired by the Holistically-nested Edge Detection (HED)
network. Most of the existing methods in the literature are based on handcrafted
models such as straight-line, curve-based techniques or a combination of both. Unfortunately, such models are insufficient when dealing with complex shape variations of the pectoral muscle boundary and when the boundary is unclear due to overlapping breast tissue. To compensate for these issues, we propose a neural network framework that incorporates multi-scale and multi-level learning, capable of learning complex hierarchical features to resolve spatial ambiguity in estimating the pectoral muscle boundary. For this purpose, we modified the HED network architecture to specifically find `contour-like' objects in mammograms. The proposed framework produced a probability map that can be used to estimate the initial pectoral muscle boundary. Subsequently, we process these maps by extracting morphological properties to find the actual pectoral muscle boundary. Finally, we developed two different post-processing steps to find the actual pectoral muscle boundary. Quantitative evaluation results show that the proposed method is comparable with alternative state-of-the-art methods producing on average values of 94:8 +/- 8:5% and 97:5 +/- 6:3% for the Jaccard and Dice similarity metrics, respectively, across four different databases.
Iaith wreiddiolSaesneg
Tudalennau (o-i)1-17
Nifer y tudalennau17
CyfnodolynMedical Image Analysis
Dyddiad ar-lein cynnar20 Meh 2019
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 31 Hyd 2019

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