Lung Nodule Classification using Deep Local-Global Networks

23 Apr 2019Mundher Al-ShabiBoon Leong LanWai Yee ChanKwan-Hoong NgMaxine Tan

Purpose: Lung nodules have very diverse shapes and sizes, which makes classifying them as benign/malignant a challenging problem. In this paper, we propose a novel method to predict the malignancy of nodules that have the capability to analyze the shape and size of a nodule using a global feature extractor, as well as the density and structure of the nodule using a local feature extractor... (read more)

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Evaluation Results from the Paper


#2 best model for Lung Nodule Classification on LIDC-IDRI (Accuracy(10-fold) metric)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Lung Nodule Classification LIDC-IDRI Local-Global Accuracy(10-fold) 88.46 # 2
Lung Nodule Classification LIDC-IDRI Local-Global AUC 95.62 # 2