CoLe-CNN: Context-learning convolutional neural network with adaptive loss function for lung nodule segmentation.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: An accurate segmentation of lung nodules in computed tomography images is a crucial step for the physical characterization of the tumour. Being often completely manually accomplished, nodule segmentation turns to be a tedious and time-consuming procedure and this represents a high obstacle in clinical practice. In this paper, we propose a novel Convolutional Neural Network for nodule segmentation that combines a light and efficient architecture with innovative loss function and segmentation strategy.

Authors

  • Giuseppe Pezzano
    Eurecat, Centre Tecnològic de Catalunya, eHealth Unit, Barcelona, Spain; Universitat de Barcelona, Department of Mathematics and Computer Science, Barcelona, Spain. Electronic address: giuseppe.pezzano@eurecat.org.
  • Vicent Ribas Ripoll
    Eurecat, Centre Tecnològic de Catalunya, eHealth Unit, Barcelona, Spain.
  • Petia Radeva
    Dept. Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain; Computer Vision Center (CVC), Barcelona, Spain.